{smcl}
{com}{sf}{ul off}{txt}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}F:\My files\Survey experiment\Decoupling research note\Analysis\May 2017 resubmitted replication files\De Rooij et al. 2017 PSRM replication log_May 5 2017.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res} 5 May 2017, 12:56:42

{com}. do "C:\Users\Eline\AppData\Local\Temp\STD00000000.tmp"
{txt}
{com}. *****************************************************************************************************************
. * Files for the replication of "The Differential Impact of Threats on Ethnic Prejudice toward 
. *       Three Minority Groups in Britain"
. * Eline A. de Rooij, Matthew J. Goodwin, and Mark Pickup
. * Political Science Research and Methods (PSRM)  
. * Date: May 5 2017
. 
. *****************************************************************************************************************
. *   2011 Analysis       
. *****************************************************************************************************************
. 
. * The following analyses were carried out using Stata/SE 14.2 for Windows (64-bit x86-64) 
. 
. * download .dta files into new personal folder and specify it as the working directory:
. cd "F:\My files\Survey experiment\Decoupling research note\Analysis\May 2017 resubmitted replication files"
{res}F:\My files\Survey experiment\Decoupling research note\Analysis\May 2017 resubmitted replication files
{txt}
{com}. ** NOTE: insert correct link to folder between " " 
. 
. 
. * open data (from folder set as working directory):
. use "De Rooij et al. 2017 PSRM replication_2011.dta" , clear
{txt}
{com}. 
. 
. *********************************************************************
. * RECODES
. *********************************************************************
. 
. * create treatment variable for coupled/decoupled threat items
. gen treatment = 1 if G1s1 == 1
{txt}(673 missing values generated)

{com}. replace treatment = 0 if G2s2 == 1
{txt}(673 real changes made)

{com}. label var treatment "received coupled threat items"
{txt}
{com}. label define treatl 0 "received decoupled items" 1 "received coupled items"
{txt}
{com}. label value treatment treatl
{txt}
{com}. 
. * threat1
. gen threat1 = g1q1
{txt}
{com}. replace threat1 = g2q1 if g2q1<=5
{txt}(673 real changes made)

{com}. recode threat1 (5=.) (1=4) (4=1) (2=3) (3=2)
{txt}(threat1: 1097 changes made)

{com}. 
. * threat2
. gen threat2 = g1q2
{txt}
{com}. replace threat2 = g2q2 if g2q2<=5
{txt}(673 real changes made)

{com}. recode threat2 (5=.) (1=4) (4=1) (2=3) (3=2)
{txt}(threat2: 1097 changes made)

{com}. 
. * threat3
. gen threat3 = g1q3
{txt}
{com}. replace threat3 = g2q3 if g2q3<=5
{txt}(673 real changes made)

{com}. recode threat3 (5=.) (1=4) (4=1) (2=3) (3=2)
{txt}(threat3: 1097 changes made)

{com}. 
. * threat4
. gen threat4 = g1q4
{txt}
{com}. replace threat4 = g2q4 if g2q4<=5
{txt}(673 real changes made)

{com}. recode threat4 (5=.) (1=4) (4=1) (2=3) (3=2)
{txt}(threat4: 1097 changes made)

{com}. 
. * threat5
. gen threat5 = g1q5
{txt}
{com}. replace threat5 = g2q5 if g2q5<=5
{txt}(673 real changes made)

{com}. recode threat5 (5=.) (1=4) (4=1) (2=3) (3=2)
{txt}(threat5: 1097 changes made)

{com}. 
. * threat6
. gen threat6 = g1q6
{txt}
{com}. replace threat6 = g2q6 if g2q6<=5
{txt}(673 real changes made)

{com}. recode threat6 (5=.) 
{txt}(threat6: 142 changes made)

{com}. 
. * threat7
. gen threat7 = g1q7
{txt}
{com}. replace threat7 = g2q7 if g2q7<=5
{txt}(673 real changes made)

{com}. recode threat7 (5=.) 
{txt}(threat7: 194 changes made)

{com}. 
. label var threat1 "Violence in Neighbourhood"
{txt}
{com}. label var threat2 "Individual Economic"
{txt}
{com}. label var threat3 "Violence in Society"
{txt}
{com}. label var threat4 "British Culture"
{txt}
{com}. label var threat5 "Collective Economic"
{txt}
{com}. label var threat6 "Britain Better"
{txt}
{com}. label var threat7 "Neighbourhood Nicer"
{txt}
{com}. 
. label define threatl 1 "strongly disagree" 2 "tend to disagree" 3 "tend to agree" 4 "strongly agree"
{txt}
{com}. label value threat1 threatl
{txt}
{com}. label value threat2 threatl
{txt}
{com}. label value threat3 threatl
{txt}
{com}. label value threat4 threatl
{txt}
{com}. label value threat5 threatl
{txt}
{com}. label define threatl2 4 "strongly disagree" 3 "tend to disagree" 2 "tend to agree" 1 "strongly agree"
{txt}
{com}. label value threat6 threatl2
{txt}
{com}. label value threat7 threatl2
{txt}
{com}. 
. * economy
. gen retrofin = fiq1
{txt}
{com}. recode retrofin(6=.)
{txt}(retrofin: 25 changes made)

{com}. label var retrofin "financial situation of household compared to 12 months ago"
{txt}
{com}. label define retrofin 1 "got a lot worse" 2 "got a little worse" 3 "stay the same" 4 "got a little better" 5 "got a lot better"
{txt}
{com}. label value retrofin retrofin
{txt}
{com}. 
. gen retroecon = fiq2
{txt}
{com}. recode retroecon (6=.)
{txt}(retroecon: 39 changes made)

{com}. label var retroecon "general economic situation in country compared to 12 months ago"
{txt}
{com}. label define retroecon 1 "got a lot worse" 2 "got a little worse" 3 "stay the same" 4 "got a little better" 5 "got a lot better"
{txt}
{com}. label value retroecon retroecon
{txt}
{com}. 
. gen prosfin = fiq3
{txt}
{com}. recode prosfin(6=.)
{txt}(prosfin: 56 changes made)

{com}. label var prosfin "expected change of financial situation of household"
{txt}
{com}. label define prosfin 1 "get a lot worse" 2 "get a little worse" 3 "stay the same" 4 "get a little better" 5 "get a lot better"
{txt}
{com}. label value prosfin prosfin
{txt}
{com}. 
. gen prosecon = fiq4
{txt}
{com}. recode prosecon (6=.)
{txt}(prosecon: 69 changes made)

{com}. label var prosecon "expected change of economic situation in country"
{txt}
{com}. label define prosecon 1 "get a lot worse" 2 "get a little worse" 3 "stay the same" 4 "get a little better" 5 "get a lot better"
{txt}
{com}. label value prosecon prosecon
{txt}
{com}. 
. * education
. gen edu_age=Education_age
{txt}
{com}. recode edu_age (7=.) (1=15) (2=16) (3=17.5) (4=19) (5=20)
{txt}(edu_age: 1009 changes made)

{com}. replace edu_age=Age if edu_age==6
{txt}(88 real changes made)

{com}. recode edu_age (21/100 = 20)
{txt}(edu_age: 50 changes made)

{com}. label var edu_age "terminal age of education"
{txt}
{com}. 
. * age already exists (no missing)
. tab Age

        {txt}Age {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
         18 {c |}{res}         14        1.28        1.28
{txt}         19 {c |}{res}         15        1.37        2.64
{txt}         20 {c |}{res}         16        1.46        4.10
{txt}         21 {c |}{res}         18        1.64        5.74
{txt}         22 {c |}{res}         20        1.82        7.57
{txt}         23 {c |}{res}         27        2.46       10.03
{txt}         24 {c |}{res}         32        2.92       12.94
{txt}         25 {c |}{res}         14        1.28       14.22
{txt}         26 {c |}{res}         14        1.28       15.50
{txt}         27 {c |}{res}         16        1.46       16.96
{txt}         28 {c |}{res}         16        1.46       18.41
{txt}         29 {c |}{res}         21        1.91       20.33
{txt}         30 {c |}{res}         26        2.37       22.70
{txt}         31 {c |}{res}         19        1.73       24.43
{txt}         32 {c |}{res}         19        1.73       26.16
{txt}         33 {c |}{res}         24        2.19       28.35
{txt}         34 {c |}{res}         20        1.82       30.17
{txt}         35 {c |}{res}         22        2.01       32.18
{txt}         36 {c |}{res}         16        1.46       33.64
{txt}         37 {c |}{res}         17        1.55       35.19
{txt}         38 {c |}{res}         18        1.64       36.83
{txt}         39 {c |}{res}         11        1.00       37.83
{txt}         40 {c |}{res}         16        1.46       39.29
{txt}         41 {c |}{res}         16        1.46       40.75
{txt}         42 {c |}{res}         14        1.28       42.02
{txt}         43 {c |}{res}         14        1.28       43.30
{txt}         44 {c |}{res}         11        1.00       44.30
{txt}         45 {c |}{res}         17        1.55       45.85
{txt}         46 {c |}{res}         25        2.28       48.13
{txt}         47 {c |}{res}         14        1.28       49.41
{txt}         48 {c |}{res}          9        0.82       50.23
{txt}         49 {c |}{res}         15        1.37       51.60
{txt}         50 {c |}{res}         15        1.37       52.96
{txt}         51 {c |}{res}         15        1.37       54.33
{txt}         52 {c |}{res}         18        1.64       55.97
{txt}         53 {c |}{res}         13        1.19       57.16
{txt}         54 {c |}{res}         18        1.64       58.80
{txt}         55 {c |}{res}         24        2.19       60.98
{txt}         56 {c |}{res}         24        2.19       63.17
{txt}         57 {c |}{res}         27        2.46       65.63
{txt}         58 {c |}{res}         35        3.19       68.82
{txt}         59 {c |}{res}         24        2.19       71.01
{txt}         60 {c |}{res}         27        2.46       73.47
{txt}         61 {c |}{res}         21        1.91       75.39
{txt}         62 {c |}{res}         26        2.37       77.76
{txt}         63 {c |}{res}         30        2.73       80.49
{txt}         64 {c |}{res}         36        3.28       83.77
{txt}         65 {c |}{res}         26        2.37       86.14
{txt}         66 {c |}{res}         16        1.46       87.60
{txt}         67 {c |}{res}         23        2.10       89.70
{txt}         68 {c |}{res}         25        2.28       91.98
{txt}         69 {c |}{res}         14        1.28       93.25
{txt}         70 {c |}{res}         11        1.00       94.26
{txt}         71 {c |}{res}         14        1.28       95.53
{txt}         72 {c |}{res}         11        1.00       96.54
{txt}         73 {c |}{res}          5        0.46       96.99
{txt}         74 {c |}{res}          4        0.36       97.36
{txt}         75 {c |}{res}          7        0.64       97.99
{txt}         76 {c |}{res}          4        0.36       98.36
{txt}         77 {c |}{res}          4        0.36       98.72
{txt}         78 {c |}{res}          4        0.36       99.09
{txt}         79 {c |}{res}          3        0.27       99.36
{txt}         80 {c |}{res}          3        0.27       99.64
{txt}         81 {c |}{res}          1        0.09       99.73
{txt}         82 {c |}{res}          2        0.18       99.91
{txt}         84 {c |}{res}          1        0.09      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}      1,097      100.00
{txt}
{com}. 
. * female (no missing)
. recode Gender (1=0 "male") (2=1 "female"), into(female)
{txt}(1097 differences between Gender and female)

{com}. 
. * social grade already exists (no missing)
. tab SocialGrade

     {txt}Social {c |}
      Grade {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
         AB {c |}{res}        410       37.37       37.37
{txt}         C1 {c |}{res}        332       30.26       67.64
{txt}         C2 {c |}{res}        142       12.94       80.58
{txt}         DE {c |}{res}        213       19.42      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}      1,097      100.00
{txt}
{com}. 
. * work status already exists, but 31 missing (coded with missing value code .a)
. ** Note: to be recoded after imputation
. tab Work_status

                         {txt}Working status {c |}      Freq.     Percent        Cum.
{hline 40}{c +}{hline 35}
Working full time (30 or more hours per {c |}{res}        452       42.40       42.40
{txt}Working part time (8-29 hours a week)   {c |}{res}        128       12.01       54.41
{txt}Working part time (Less than 8 hours a  {c |}{res}         20        1.88       56.29
{txt}                    Full Time student   {c |}{res}         64        6.00       62.29
{txt}                              Retired   {c |}{res}        260       24.39       86.68
{txt}                           Unemployed   {c |}{res}         43        4.03       90.71
{txt}                          Not working   {c |}{res}         99        9.29      100.00
{txt}{hline 40}{c +}{hline 35}
                                  Total {c |}{res}      1,066      100.00
{txt}
{com}. 
. * UKborn
. recode Born (1=1 "inside the UK (ENG, WAL, SCO, NIR)") (2=0 "outside the UK") (3=.), gen(UKborn)
{txt}(73 differences between Born and UKborn)

{com}. label var UKborn "born inside the UK"
{txt}
{com}. 
. * ethnicity already exists
. tab Ethnicity if Ethnicity<2

  {txt}To which of these groups {c |}
       do you consider you {c |}
                   belong? {c |}      Freq.     Percent        Cum.
{hline 27}{c +}{hline 35}
             White British {c |}{res}        929      100.00      100.00
{txt}{hline 27}{c +}{hline 35}
                     Total {c |}{res}        929      100.00
{txt}
{com}. * white British only
. 
. * British identity: NOTE: Mark used only one question (g13q2) in riots paper... ?
. recode g13q1 (5=.) (1=4) (4=1) (2=3) (3=2), gen(Bid1)
{txt}(1097 differences between g13q1 and Bid1)

{com}. recode g13q2 (5=.) (1=4) (4=1) (2=3) (3=2), gen(Bid2)
{txt}(1097 differences between g13q2 and Bid2)

{com}. recode g13q3 (5=.) (1=4) (4=1) (2=3) (3=2), gen(Bid3)
{txt}(1097 differences between g13q3 and Bid3)

{com}. recode g13q4 (5=.) (1=4) (4=1) (2=3) (3=2), gen(Bid4)
{txt}(1097 differences between g13q4 and Bid4)

{com}. label define Bidl 1 "strongly disagree" 2 "tend to disagree" 3 "tend to agree" 4 "strongly agree"
{txt}
{com}. label value Bid1 Bidl
{txt}
{com}. label value Bid2 Bidl
{txt}
{com}. label value Bid3 Bidl
{txt}
{com}. label value Bid4 Bidl
{txt}
{com}. 
. * authoritarianism
. recode g11q1 (5=.) (1=4) (4=1) (2=3) (3=2), gen(auth1)
{txt}(1097 differences between g11q1 and auth1)

{com}. recode g11q2 (5=.) (1=4) (4=1) (2=3) (3=2), gen(auth2)
{txt}(1097 differences between g11q2 and auth2)

{com}. recode g11q3 (5=.) (1=4) (4=1) (2=3) (3=2), gen(auth3)
{txt}(1097 differences between g11q3 and auth3)

{com}. label define authl 1 "strongly disagree" 2 "tend to disagree" 3 "tend to agree" 4 "strongly agree"
{txt}
{com}. label value auth1 authl
{txt}
{com}. label value auth2 authl
{txt}
{com}. label value auth3 authl
{txt}
{com}. 
. * self-esteem
. recode g12q1 (1=1 "True") (2=0 "False") (3=.), gen(est1)
{txt}(874 differences between g12q1 and est1)

{com}. recode g12q2 (1=1 "True") (2=0 "False") (3=.), gen(est2)
{txt}(849 differences between g12q2 and est2)

{com}. recode g12q3 (1=1 "True") (2=0 "False") (3=.), gen(est3)
{txt}(599 differences between g12q3 and est3)

{com}. recode g12q4 (1=1 "True") (2=0 "False") (3=.), gen(est4)
{txt}(932 differences between g12q4 and est4)

{com}. recode g12q5 (1=1 "True") (2=0 "False") (3=.), gen(est5)
{txt}(727 differences between g12q5 and est5)

{com}. 
. * group hostility
. recode g7q1 (5=.) (1=1) (2=2) (3=3) (4=4), gen(GHbb1)
{txt}(299 differences between g7q1 and GHbb1)

{com}. recode g7q2 (5=.) (1=4) (4=1) (2=3) (3=2), gen(GHbb2)
{txt}(1097 differences between g7q2 and GHbb2)

{com}. recode g7q3 (5=.) (1=1) (2=2) (3=3) (4=4), gen(GHbb3)
{txt}(271 differences between g7q3 and GHbb3)

{com}. recode g7q4 (5=.) (1=4) (4=1) (2=3) (3=2), gen(GHbb4)
{txt}(1097 differences between g7q4 and GHbb4)

{com}. recode g7q5 (5=.) (1=4) (4=1) (2=3) (3=2), gen(GHbb5)
{txt}(1097 differences between g7q5 and GHbb5)

{com}. recode g7q6 (5=.) (1=4) (4=1) (2=3) (3=2), gen(GHbb6)
{txt}(1097 differences between g7q6 and GHbb6)

{com}. recode g7q7 (5=.) (1=4) (4=1) (2=3) (3=2), gen(GHbb7)
{txt}(1097 differences between g7q7 and GHbb7)

{com}. recode g7q8 (5=.) (1=4) (4=1) (2=3) (3=2), gen(GHbb8)
{txt}(1097 differences between g7q8 and GHbb8)

{com}. 
. recode g8q1 (5=.) (1=1) (2=2) (3=3) (4=4), gen(GHmu1)
{txt}(295 differences between g8q1 and GHmu1)

{com}. recode g8q2 (5=.) (1=4) (4=1) (2=3) (3=2), gen(GHmu2)
{txt}(1097 differences between g8q2 and GHmu2)

{com}. recode g8q3 (5=.) (1=1) (2=2) (3=3) (4=4), gen(GHmu3)
{txt}(268 differences between g8q3 and GHmu3)

{com}. recode g8q4 (5=.) (1=4) (4=1) (2=3) (3=2), gen(GHmu4)
{txt}(1097 differences between g8q4 and GHmu4)

{com}. recode g8q5 (5=.) (1=4) (4=1) (2=3) (3=2), gen(GHmu5)
{txt}(1097 differences between g8q5 and GHmu5)

{com}. recode g8q6 (5=.) (1=4) (4=1) (2=3) (3=2), gen(GHmu6)
{txt}(1097 differences between g8q6 and GHmu6)

{com}. recode g8q7 (5=.) (1=4) (4=1) (2=3) (3=2), gen(GHmu7)
{txt}(1097 differences between g8q7 and GHmu7)

{com}. recode g8q8 (5=.) (1=4) (4=1) (2=3) (3=2), gen(GHmu8)
{txt}(1097 differences between g8q8 and GHmu8)

{com}. 
. recode g9q1 (5=.) (1=1) (2=2) (3=3) (4=4), gen(GHee1)
{txt}(337 differences between g9q1 and GHee1)

{com}. recode g9q2 (5=.) (1=4) (4=1) (2=3) (3=2), gen(GHee2)
{txt}(1097 differences between g9q2 and GHee2)

{com}. recode g9q3 (5=.) (1=1) (2=2) (3=3) (4=4), gen(GHee3)
{txt}(332 differences between g9q3 and GHee3)

{com}. recode g9q4 (5=.) (1=4) (4=1) (2=3) (3=2), gen(GHee4)
{txt}(1097 differences between g9q4 and GHee4)

{com}. recode g9q5 (5=.) (1=4) (4=1) (2=3) (3=2), gen(GHee5)
{txt}(1097 differences between g9q5 and GHee5)

{com}. recode g9q6 (5=.) (1=4) (4=1) (2=3) (3=2), gen(GHee6)
{txt}(1097 differences between g9q6 and GHee6)

{com}. recode g9q7 (5=.) (1=4) (4=1) (2=3) (3=2), gen(GHee7)
{txt}(1097 differences between g9q7 and GHee7)

{com}. recode g9q8 (5=.) (1=4) (4=1) (2=3) (3=2), gen(GHee8)
{txt}(1097 differences between g9q8 and GHee8)

{com}. 
. recode g10q1 (5=.) (1=1) (2=2) (3=3) (4=4), gen(GHwb1)
{txt}(32 differences between g10q1 and GHwb1)

{com}. recode g10q2 (5=.) (1=4) (4=1) (2=3) (3=2), gen(GHwb2)
{txt}(933 differences between g10q2 and GHwb2)

{com}. recode g10q3 (5=.) (1=1) (2=2) (3=3) (4=4), gen(GHwb3)
{txt}(31 differences between g10q3 and GHwb3)

{com}. recode g10q4 (5=.) (1=4) (4=1) (2=3) (3=2), gen(GHwb4)
{txt}(898 differences between g10q4 and GHwb4)

{com}. recode g10q5 (5=.) (1=4) (4=1) (2=3) (3=2), gen(GHwb5)
{txt}(942 differences between g10q5 and GHwb5)

{com}. recode g10q6 (5=.) (1=4) (4=1) (2=3) (3=2), gen(GHwb6)
{txt}(919 differences between g10q6 and GHwb6)

{com}. recode g10q7 (5=.) (1=4) (4=1) (2=3) (3=2), gen(GHwb7)
{txt}(920 differences between g10q7 and GHwb7)

{com}. recode g10q8 (5=.) (1=4) (4=1) (2=3) (3=2), gen(GHwb8)
{txt}(941 differences between g10q8 and GHwb8)

{com}. 
. * social distance 
. recode g4q1 (5=.) (1=1 "very attractive") (2=2 "fairly attractive") (3=3 "fairly unattractive") (4=4 "very unattractive"), gen(SDbb1)
{txt}(390 differences between g4q1 and SDbb1)

{com}. recode g4q2 (5=.) (1=1 "very attractive") (2=2 "fairly attractive") (3=3 "fairly unattractive") (4=4 "very unattractive"), gen(SDbb2)
{txt}(433 differences between g4q2 and SDbb2)

{com}. recode g4q3 (5=.) (1=1 "very attractive") (2=2 "fairly attractive") (3=3 "fairly unattractive") (4=4 "very unattractive"), gen(SDbb3)
{txt}(421 differences between g4q3 and SDbb3)

{com}. 
. recode g5q1 (5=.) (1=1 "very attractive") (2=2 "fairly attractive") (3=3 "fairly unattractive") (4=4 "very unattractive"), gen(SDmu1)
{txt}(372 differences between g5q1 and SDmu1)

{com}. recode g5q2 (5=.) (1=1 "very attractive") (2=2 "fairly attractive") (3=3 "fairly unattractive") (4=4 "very unattractive"), gen(SDmu2)
{txt}(411 differences between g5q2 and SDmu2)

{com}. recode g5q3 (5=.) (1=1 "very attractive") (2=2 "fairly attractive") (3=3 "fairly unattractive") (4=4 "very unattractive"), gen(SDmu3)
{txt}(376 differences between g5q3 and SDmu3)

{com}. 
. recode g6q1 (5=.) (1=1 "very attractive") (2=2 "fairly attractive") (3=3 "fairly unattractive") (4=4 "very unattractive"), gen(SDee1)
{txt}(389 differences between g6q1 and SDee1)

{com}. recode g6q2 (5=.) (1=1 "very attractive") (2=2 "fairly attractive") (3=3 "fairly unattractive") (4=4 "very unattractive"), gen(SDee2)
{txt}(429 differences between g6q2 and SDee2)

{com}. recode g6q3 (5=.) (1=1 "very attractive") (2=2 "fairly attractive") (3=3 "fairly unattractive") (4=4 "very unattractive"), gen(SDee3)
{txt}(429 differences between g6q3 and SDee3)

{com}. 
. 
. *********************************************************************
. * TABLE A.2A IN THE APPENDIX:
. *       Descriptive Statistics of Independent Variables, 2011 
. *       (before multiple imputation) 
. *********************************************************************
. 
. * keep only White British respondents:
. keep if Ethnicity==1
{txt}(168 observations deleted)

{com}. * Note: 168 respondents deleted
. 
. * descriptives before imputation, for non-imputed variables only
. ** NOTE: temporarily create i.work_status and Bidentity_2, then delete and re-do after imputation
. 
. * work status (already 31 missing in original code (coded with missing value code .a)
. recode Work_status (1=1) (2/3 =2) (4=3) (5=4) (6=5) (7/8 = 6), into(work_status)
{txt}(418 differences between Work_status and work_status)

{com}. label define work_status 1 "working full time" 2 "working part time" 3 "full time student" 4 "retired" 5 "unemployed" 6 "not working"
{txt}
{com}. label value work_status work_status
{txt}
{com}. label var work_status "working status"
{txt}
{com}. * British identity
. egen Bidentity_2 = rowmean(Bid1-Bid4)
{txt}(22 missing values generated)

{com}. 
. * decoupled threats:
. sum threat1 threat2 threat3 threat4 threat5 if treatment==0

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 5}threat1 {c |}{res}        539    2.434137     .845293          1          4
{txt}{space 5}threat2 {c |}{res}        536    2.994403    .7349527          1          4
{txt}{space 5}threat3 {c |}{res}        539    2.862709    .8291175          1          4
{txt}{space 5}threat4 {c |}{res}        542      3.0369     .909248          1          4
{txt}{space 5}threat5 {c |}{res}        547    3.142596    .6696967          1          4
{txt}
{com}. * coupled threats:
. sum threat1 threat2 threat3 threat4 threat5 if treatment==1

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 5}threat1 {c |}{res}        320    2.184375    .9923246          1          4
{txt}{space 5}threat2 {c |}{res}        311    2.360129    1.024956          1          4
{txt}{space 5}threat3 {c |}{res}        318    2.512579     1.01324          1          4
{txt}{space 5}threat4 {c |}{res}        324    2.805556    1.085722          1          4
{txt}{space 5}threat5 {c |}{res}        315    2.612698    1.038662          1          4
{txt}
{com}. * other:
. sum female Age edu_age i.SocialGrade i.work_status UKborn Bidentity_2 retroecon retrofin 

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 6}female {c |}{res}        929    .5468245    .4980708          0          1
{txt}{space 9}Age {c |}{res}        929    47.79225    16.53852         18         84
{txt}{space 5}edu_age {c |}{res}        926    17.88175     1.89503         15         20
{txt}{space 12} {c |}
{space 1}SocialGrade {c |}
{space 9}C1  {c |}{res}        929    .2938644    .4557759          0          1
{txt}{hline 13}{c +}{hline 57}
{space 9}C2  {c |}{res}        929    .1302476    .3367569          0          1
{txt}{space 9}DE  {c |}{res}        929    .1959096     .397113          0          1
{txt}{space 12} {c |}
{space 1}work_status {c |}
working p..  {c |}{res}        907    .1411246    .3483421          0          1
{txt}full time..  {c |}{res}        907    .0529217    .2240007          0          1
{txt}{hline 13}{c +}{hline 57}
{space 4}retired  {c |}{res}        907    .2557883    .4365441          0          1
{txt}{space 1}unemployed  {c |}{res}        907    .0418964    .2004629          0          1
{txt}not working  {c |}{res}        907    .0937155    .2915934          0          1
{txt}{space 12} {c |}
{space 6}UKborn {c |}{res}        928    .9849138    .1219616          0          1
{txt}{space 1}Bidentity_2 {c |}{res}        907    3.132764    .6272792          1          4
{txt}{hline 13}{c +}{hline 57}
{space 3}retroecon {c |}{res}        900    2.034444    .9361913          1          5
{txt}{space 4}retrofin {c |}{res}        914    2.269147       .8916          1          5
{txt}
{com}. ** to obtain descriptives for first categories of SocialGrade and work_status:
. sum ib(last).SocialGrade ib(last).work_status 

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 1}SocialGrade {c |}
{space 9}AB  {c |}{res}        929    .3799785    .4856426          0          1
{txt}{space 9}C1  {c |}{res}        929    .2938644    .4557759          0          1
{txt}{space 9}C2  {c |}{res}        929    .1302476    .3367569          0          1
{txt}{space 12} {c |}
{space 1}work_status {c |}
working f..  {c |}{res}        907    .4145535    .4929166          0          1
{txt}{hline 13}{c +}{hline 57}
working p..  {c |}{res}        907    .1411246    .3483421          0          1
{txt}full time..  {c |}{res}        907    .0529217    .2240007          0          1
{txt}{space 4}retired  {c |}{res}        907    .2557883    .4365441          0          1
{txt}{space 1}unemployed  {c |}{res}        907    .0418964    .2004629          0          1
{txt}
{com}. 
. drop work_status Bidentity_2
{txt}
{com}. 
. 
. *********************************************************************
. * TABLE A.4A IN THE APPENDIX:  
. *       Associations between Threats under Coupled and Decoupled Conditions, 2011
. *********************************************************************
. 
. * In order to estimate correlations and their level of significance with survey data:
. * (1) use correlate with aweights for point estimates of the correlation
. * (2) use svy: regress for p-values 
. *       Do svy: regress y x and svy: regress x y and take the biggest p-value, which is the conservative thing to do
. 
. * decoupled
. pwcorr threat1 threat2 threat3 threat4 threat5 if treatment==0 [aweight=W8], sig obs

             {txt}{c |}  threat1  threat2  threat3  threat4  threat5
{hline 13}{c +}{hline 45}
     threat1 {c |} {res}  1.0000 
             {txt}{c |}
             {c |}{res}      539
             {txt}{c |}
     threat2 {c |} {res}  0.3682   1.0000 
             {txt}{c |}{res}   0.0000
             {txt}{c |}{res}      523      536
             {txt}{c |}
     threat3 {c |} {res}  0.6679   0.4079   1.0000 
             {txt}{c |}{res}   0.0000   0.0000
             {txt}{c |}{res}      527      525      539
             {txt}{c |}
     threat4 {c |} {res}  0.3701   0.2352   0.4612   1.0000 
             {txt}{c |}{res}   0.0000   0.0000   0.0000
             {txt}{c |}{res}      527      524      528      542
             {txt}{c |}
     threat5 {c |} {res}  0.3328   0.5336   0.3660   0.1765   1.0000 
             {txt}{c |}{res}   0.0000   0.0000   0.0000   0.0000
             {txt}{c |}{res}      532      530      533      535      547
             {txt}{c |}

{com}. * coupled
. pwcorr threat1 threat2 threat3 threat4 threat5 if treatment==1 [aweight=W8], sig obs

             {txt}{c |}  threat1  threat2  threat3  threat4  threat5
{hline 13}{c +}{hline 45}
     threat1 {c |} {res}  1.0000 
             {txt}{c |}
             {c |}{res}      320
             {txt}{c |}
     threat2 {c |} {res}  0.6130   1.0000 
             {txt}{c |}{res}   0.0000
             {txt}{c |}{res}      301      311
             {txt}{c |}
     threat3 {c |} {res}  0.6937   0.6661   1.0000 
             {txt}{c |}{res}   0.0000   0.0000
             {txt}{c |}{res}      310      300      318
             {txt}{c |}
     threat4 {c |} {res}  0.6080   0.6550   0.7081   1.0000 
             {txt}{c |}{res}   0.0000   0.0000   0.0000
             {txt}{c |}{res}      311      304      310      324
             {txt}{c |}
     threat5 {c |} {res}  0.6554   0.7675   0.7037   0.7872   1.0000 
             {txt}{c |}{res}   0.0000   0.0000   0.0000   0.0000
             {txt}{c |}{res}      303      301      306      308      315
             {txt}{c |}

{com}. svyset [pweight=W8]

      {txt}pweight:{col 16}{res}W8
          {txt}VCE:{col 16}{res}linearized
  {txt}Single unit:{col 16}{res}missing
     {txt}Strata 1:{col 16}<one>
         SU 1:{col 16}<observations>
        FPC 1:{col 16}<zero>
{p2colreset}{...}

{com}. svy: reg threat1 threat2 if treatment==0 
{txt}(running regress on estimation sample)
{res}
{txt}Survey: Linear regression

{col 1}Number of strata{col 20}= {res}        1{txt}{col 49}Number of obs{col 67}= {res}       523
{txt}{col 1}Number of PSUs{col 20}= {res}      523{txt}{col 49}Population size{col 67}={res} 524.558789
{txt}{col 49}Design df{col 67}= {res}       522
{txt}{col 49}F({res}   1{txt},{res}    522{txt}){col 67}= {res}     69.52
{txt}{col 49}Prob > F{col 67}= {res}    0.0000
{txt}{col 49}R-squared{col 67}= {res}    0.1355

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}  Linearized
{col 1}     threat1{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}threat2 {c |}{col 14}{res}{space 2} .4303137{col 26}{space 2} .0516081{col 37}{space 1}    8.34{col 46}{space 3}0.000{col 54}{space 4} .3289286{col 67}{space 3} .5316987
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}  1.16283{col 26}{space 2} .1529464{col 37}{space 1}    7.60{col 46}{space 3}0.000{col 54}{space 4} .8623641{col 67}{space 3} 1.463296
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. svy: reg threat2 threat1 if treatment==0 
{txt}(running regress on estimation sample)
{res}
{txt}Survey: Linear regression

{col 1}Number of strata{col 20}= {res}        1{txt}{col 49}Number of obs{col 67}= {res}       523
{txt}{col 1}Number of PSUs{col 20}= {res}      523{txt}{col 49}Population size{col 67}={res} 524.558789
{txt}{col 49}Design df{col 67}= {res}       522
{txt}{col 49}F({res}   1{txt},{res}    522{txt}){col 67}= {res}     67.98
{txt}{col 49}Prob > F{col 67}= {res}    0.0000
{txt}{col 49}R-squared{col 67}= {res}    0.1355

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}  Linearized
{col 1}     threat2{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}threat1 {c |}{col 14}{res}{space 2}   .31497{col 26}{space 2} .0382009{col 37}{space 1}    8.25{col 46}{space 3}0.000{col 54}{space 4} .2399236{col 67}{space 3} .3900164
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 2.236581{col 26}{space 2} .1019704{col 37}{space 1}   21.93{col 46}{space 3}0.000{col 54}{space 4} 2.036258{col 67}{space 3} 2.436904
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. svy: reg threat1 threat3 if treatment==0 
{txt}(running regress on estimation sample)
{res}
{txt}Survey: Linear regression

{col 1}Number of strata{col 20}= {res}        1{txt}{col 49}Number of obs{col 67}= {res}       527
{txt}{col 1}Number of PSUs{col 20}= {res}      527{txt}{col 49}Population size{col 67}={res} 528.424701
{txt}{col 49}Design df{col 67}= {res}       526
{txt}{col 49}F({res}   1{txt},{res}    526{txt}){col 67}= {res}    376.57
{txt}{col 49}Prob > F{col 67}= {res}    0.0000
{txt}{col 49}R-squared{col 67}= {res}    0.4461

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}  Linearized
{col 1}     threat1{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}threat3 {c |}{col 14}{res}{space 2} .6839908{col 26}{space 2} .0352476{col 37}{space 1}   19.41{col 46}{space 3}0.000{col 54}{space 4} .6147475{col 67}{space 3} .7532341
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .4978694{col 26}{space 2} .0923507{col 37}{space 1}    5.39{col 46}{space 3}0.000{col 54}{space 4}  .316448{col 67}{space 3} .6792909
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. svy: reg threat3 threat1 if treatment==0 
{txt}(running regress on estimation sample)
{res}
{txt}Survey: Linear regression

{col 1}Number of strata{col 20}= {res}        1{txt}{col 49}Number of obs{col 67}= {res}       527
{txt}{col 1}Number of PSUs{col 20}= {res}      527{txt}{col 49}Population size{col 67}={res} 528.424701
{txt}{col 49}Design df{col 67}= {res}       526
{txt}{col 49}F({res}   1{txt},{res}    526{txt}){col 67}= {res}    335.70
{txt}{col 49}Prob > F{col 67}= {res}    0.0000
{txt}{col 49}R-squared{col 67}= {res}    0.4461

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}  Linearized
{col 1}     threat3{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}threat1 {c |}{col 14}{res}{space 2} .6522553{col 26}{space 2} .0355993{col 37}{space 1}   18.32{col 46}{space 3}0.000{col 54}{space 4}  .582321{col 67}{space 3} .7221896
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 1.271082{col 26}{space 2} .1057876{col 37}{space 1}   12.02{col 46}{space 3}0.000{col 54}{space 4} 1.063264{col 67}{space 3}   1.4789
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. svy: reg threat1 threat4 if treatment==0 
{txt}(running regress on estimation sample)
{res}
{txt}Survey: Linear regression

{col 1}Number of strata{col 20}= {res}        1{txt}{col 49}Number of obs{col 67}= {res}       527
{txt}{col 1}Number of PSUs{col 20}= {res}      527{txt}{col 49}Population size{col 67}={res} 529.362844
{txt}{col 49}Design df{col 67}= {res}       526
{txt}{col 49}F({res}   1{txt},{res}    526{txt}){col 67}= {res}     72.40
{txt}{col 49}Prob > F{col 67}= {res}    0.0000
{txt}{col 49}R-squared{col 67}= {res}    0.1370

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}  Linearized
{col 1}     threat1{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}threat4 {c |}{col 14}{res}{space 2} .3486704{col 26}{space 2} .0409781{col 37}{space 1}    8.51{col 46}{space 3}0.000{col 54}{space 4} .2681696{col 67}{space 3} .4291712
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 1.389708{col 26}{space 2}  .126928{col 37}{space 1}   10.95{col 46}{space 3}0.000{col 54}{space 4}  1.14036{col 67}{space 3} 1.639056
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. svy: reg threat4 threat1 if treatment==0 
{txt}(running regress on estimation sample)
{res}
{txt}Survey: Linear regression

{col 1}Number of strata{col 20}= {res}        1{txt}{col 49}Number of obs{col 67}= {res}       527
{txt}{col 1}Number of PSUs{col 20}= {res}      527{txt}{col 49}Population size{col 67}={res} 529.362844
{txt}{col 49}Design df{col 67}= {res}       526
{txt}{col 49}F({res}   1{txt},{res}    526{txt}){col 67}= {res}     74.15
{txt}{col 49}Prob > F{col 67}= {res}    0.0000
{txt}{col 49}R-squared{col 67}= {res}    0.1370

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}  Linearized
{col 1}     threat4{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}threat1 {c |}{col 14}{res}{space 2} .3928543{col 26}{space 2} .0456231{col 37}{space 1}    8.61{col 46}{space 3}0.000{col 54}{space 4} .3032285{col 67}{space 3} .4824802
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 2.078825{col 26}{space 2} .1232313{col 37}{space 1}   16.87{col 46}{space 3}0.000{col 54}{space 4} 1.836739{col 67}{space 3}  2.32091
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. svy: reg threat1 threat5 if treatment==0
{txt}(running regress on estimation sample)
{res}
{txt}Survey: Linear regression

{col 1}Number of strata{col 20}= {res}        1{txt}{col 49}Number of obs{col 67}= {res}       532
{txt}{col 1}Number of PSUs{col 20}= {res}      532{txt}{col 49}Population size{col 67}={res} 533.605492
{txt}{col 49}Design df{col 67}= {res}       531
{txt}{col 49}F({res}   1{txt},{res}    531{txt}){col 67}= {res}     36.97
{txt}{col 49}Prob > F{col 67}= {res}    0.0000
{txt}{col 49}R-squared{col 67}= {res}    0.1107

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}  Linearized
{col 1}     threat1{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}threat5 {c |}{col 14}{res}{space 2} .4277415{col 26}{space 2} .0703494{col 37}{space 1}    6.08{col 46}{space 3}0.000{col 54}{space 4} .2895443{col 67}{space 3} .5659388
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 1.110058{col 26}{space 2} .2257742{col 37}{space 1}    4.92{col 46}{space 3}0.000{col 54}{space 4}  .666538{col 67}{space 3} 1.553579
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. svy: reg threat5 threat1 if treatment==0 
{txt}(running regress on estimation sample)
{res}
{txt}Survey: Linear regression

{col 1}Number of strata{col 20}= {res}        1{txt}{col 49}Number of obs{col 67}= {res}       532
{txt}{col 1}Number of PSUs{col 20}= {res}      532{txt}{col 49}Population size{col 67}={res} 533.605492
{txt}{col 49}Design df{col 67}= {res}       531
{txt}{col 49}F({res}   1{txt},{res}    531{txt}){col 67}= {res}     57.73
{txt}{col 49}Prob > F{col 67}= {res}    0.0000
{txt}{col 49}R-squared{col 67}= {res}    0.1107

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}  Linearized
{col 1}     threat5{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}threat1 {c |}{col 14}{res}{space 2} .2588674{col 26}{space 2} .0340709{col 37}{space 1}    7.60{col 46}{space 3}0.000{col 54}{space 4} .1919371{col 67}{space 3} .3257978
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}  2.50345{col 26}{space 2} .0856743{col 37}{space 1}   29.22{col 46}{space 3}0.000{col 54}{space 4} 2.335148{col 67}{space 3} 2.671752
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. svy: reg threat2 threat3 if treatment==0
{txt}(running regress on estimation sample)
{res}
{txt}Survey: Linear regression

{col 1}Number of strata{col 20}= {res}        1{txt}{col 49}Number of obs{col 67}= {res}       525
{txt}{col 1}Number of PSUs{col 20}= {res}      525{txt}{col 49}Population size{col 67}={res} 525.801773
{txt}{col 49}Design df{col 67}= {res}       524
{txt}{col 49}F({res}   1{txt},{res}    524{txt}){col 67}= {res}     89.71
{txt}{col 49}Prob > F{col 67}= {res}    0.0000
{txt}{col 49}R-squared{col 67}= {res}    0.1664

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}  Linearized
{col 1}     threat2{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}threat3 {c |}{col 14}{res}{space 2} .3603464{col 26}{space 2} .0380456{col 37}{space 1}    9.47{col 46}{space 3}0.000{col 54}{space 4} .2856057{col 67}{space 3}  .435087
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 1.972115{col 26}{space 2} .1135249{col 37}{space 1}   17.37{col 46}{space 3}0.000{col 54}{space 4} 1.749095{col 67}{space 3} 2.195135
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. svy: reg threat3 threat2 if treatment==0
{txt}(running regress on estimation sample)
{res}
{txt}Survey: Linear regression

{col 1}Number of strata{col 20}= {res}        1{txt}{col 49}Number of obs{col 67}= {res}       525
{txt}{col 1}Number of PSUs{col 20}= {res}      525{txt}{col 49}Population size{col 67}={res} 525.801773
{txt}{col 49}Design df{col 67}= {res}       524
{txt}{col 49}F({res}   1{txt},{res}    524{txt}){col 67}= {res}     92.49
{txt}{col 49}Prob > F{col 67}= {res}    0.0000
{txt}{col 49}R-squared{col 67}= {res}    0.1664

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}  Linearized
{col 1}     threat3{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}threat2 {c |}{col 14}{res}{space 2} .4618005{col 26}{space 2} .0480175{col 37}{space 1}    9.62{col 46}{space 3}0.000{col 54}{space 4} .3674701{col 67}{space 3}  .556131
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 1.498498{col 26}{space 2}  .152409{col 37}{space 1}    9.83{col 46}{space 3}0.000{col 54}{space 4}  1.19909{col 67}{space 3} 1.797905
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. svy: reg threat2 threat4 if treatment==0 
{txt}(running regress on estimation sample)
{res}
{txt}Survey: Linear regression

{col 1}Number of strata{col 20}= {res}        1{txt}{col 49}Number of obs{col 67}= {res}       524
{txt}{col 1}Number of PSUs{col 20}= {res}      524{txt}{col 49}Population size{col 67}={res} 525.771236
{txt}{col 49}Design df{col 67}= {res}       523
{txt}{col 49}F({res}   1{txt},{res}    523{txt}){col 67}= {res}     26.12
{txt}{col 49}Prob > F{col 67}= {res}    0.0000
{txt}{col 49}R-squared{col 67}= {res}    0.0553

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}  Linearized
{col 1}     threat2{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}threat4 {c |}{col 14}{res}{space 2} .1904043{col 26}{space 2} .0372545{col 37}{space 1}    5.11{col 46}{space 3}0.000{col 54}{space 4} .1172174{col 67}{space 3} .2635911
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 2.434731{col 26}{space 2} .1188364{col 37}{space 1}   20.49{col 46}{space 3}0.000{col 54}{space 4} 2.201275{col 67}{space 3} 2.668186
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. svy: reg threat4 threat2 if treatment==0 
{txt}(running regress on estimation sample)
{res}
{txt}Survey: Linear regression

{col 1}Number of strata{col 20}= {res}        1{txt}{col 49}Number of obs{col 67}= {res}       524
{txt}{col 1}Number of PSUs{col 20}= {res}      524{txt}{col 49}Population size{col 67}={res} 525.771236
{txt}{col 49}Design df{col 67}= {res}       523
{txt}{col 49}F({res}   1{txt},{res}    523{txt}){col 67}= {res}     27.51
{txt}{col 49}Prob > F{col 67}= {res}    0.0000
{txt}{col 49}R-squared{col 67}= {res}    0.0553

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}  Linearized
{col 1}     threat4{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}threat2 {c |}{col 14}{res}{space 2} .2904734{col 26}{space 2} .0553816{col 37}{space 1}    5.24{col 46}{space 3}0.000{col 54}{space 4} .1816758{col 67}{space 3} .3992711
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 2.174165{col 26}{space 2} .1686596{col 37}{space 1}   12.89{col 46}{space 3}0.000{col 54}{space 4} 1.842832{col 67}{space 3} 2.505499
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. svy: reg threat2 threat5 if treatment==0 
{txt}(running regress on estimation sample)
{res}
{txt}Survey: Linear regression

{col 1}Number of strata{col 20}= {res}        1{txt}{col 49}Number of obs{col 67}= {res}       530
{txt}{col 1}Number of PSUs{col 20}= {res}      530{txt}{col 49}Population size{col 67}={res} 531.013885
{txt}{col 49}Design df{col 67}= {res}       529
{txt}{col 49}F({res}   1{txt},{res}    529{txt}){col 67}= {res}     55.89
{txt}{col 49}Prob > F{col 67}= {res}    0.0000
{txt}{col 49}R-squared{col 67}= {res}    0.2847

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}  Linearized
{col 1}     threat2{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}threat5 {c |}{col 14}{res}{space 2} .5792079{col 26}{space 2} .0774745{col 37}{space 1}    7.48{col 46}{space 3}0.000{col 54}{space 4} .4270126{col 67}{space 3} .7314033
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 1.199212{col 26}{space 2} .2560014{col 37}{space 1}    4.68{col 46}{space 3}0.000{col 54}{space 4}  .696308{col 67}{space 3} 1.702116
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. svy: reg threat5 threat2 if treatment==0 
{txt}(running regress on estimation sample)
{res}
{txt}Survey: Linear regression

{col 1}Number of strata{col 20}= {res}        1{txt}{col 49}Number of obs{col 67}= {res}       530
{txt}{col 1}Number of PSUs{col 20}= {res}      530{txt}{col 49}Population size{col 67}={res} 531.013885
{txt}{col 49}Design df{col 67}= {res}       529
{txt}{col 49}F({res}   1{txt},{res}    529{txt}){col 67}= {res}     99.25
{txt}{col 49}Prob > F{col 67}= {res}    0.0000
{txt}{col 49}R-squared{col 67}= {res}    0.2847

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}  Linearized
{col 1}     threat5{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}threat2 {c |}{col 14}{res}{space 2} .4914973{col 26}{space 2} .0493357{col 37}{space 1}    9.96{col 46}{space 3}0.000{col 54}{space 4} .3945794{col 67}{space 3} .5884152
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 1.658557{col 26}{space 2} .1451648{col 37}{space 1}   11.43{col 46}{space 3}0.000{col 54}{space 4} 1.373387{col 67}{space 3} 1.943728
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. svy: reg threat3 threat4 if treatment==0 
{txt}(running regress on estimation sample)
{res}
{txt}Survey: Linear regression

{col 1}Number of strata{col 20}= {res}        1{txt}{col 49}Number of obs{col 67}= {res}       528
{txt}{col 1}Number of PSUs{col 20}= {res}      528{txt}{col 49}Population size{col 67}={res} 529.771236
{txt}{col 49}Design df{col 67}= {res}       527
{txt}{col 49}F({res}   1{txt},{res}    527{txt}){col 67}= {res}    105.10
{txt}{col 49}Prob > F{col 67}= {res}    0.0000
{txt}{col 49}R-squared{col 67}= {res}    0.2127

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}  Linearized
{col 1}     threat3{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}threat4 {c |}{col 14}{res}{space 2} .4246068{col 26}{space 2} .0414179{col 37}{space 1}   10.25{col 46}{space 3}0.000{col 54}{space 4} .3432424{col 67}{space 3} .5059712
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 1.589476{col 26}{space 2} .1342682{col 37}{space 1}   11.84{col 46}{space 3}0.000{col 54}{space 4}  1.32571{col 67}{space 3} 1.853243
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. svy: reg threat4 threat3 if treatment==0 
{txt}(running regress on estimation sample)
{res}
{txt}Survey: Linear regression

{col 1}Number of strata{col 20}= {res}        1{txt}{col 49}Number of obs{col 67}= {res}       528
{txt}{col 1}Number of PSUs{col 20}= {res}      528{txt}{col 49}Population size{col 67}={res} 529.771236
{txt}{col 49}Design df{col 67}= {res}       527
{txt}{col 49}F({res}   1{txt},{res}    527{txt}){col 67}= {res}    118.70
{txt}{col 49}Prob > F{col 67}= {res}    0.0000
{txt}{col 49}R-squared{col 67}= {res}    0.2127

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}  Linearized
{col 1}     threat4{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}threat3 {c |}{col 14}{res}{space 2} .5008734{col 26}{space 2} .0459726{col 37}{space 1}   10.90{col 46}{space 3}0.000{col 54}{space 4} .4105613{col 67}{space 3} .5911856
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 1.602012{col 26}{space 2} .1420638{col 37}{space 1}   11.28{col 46}{space 3}0.000{col 54}{space 4} 1.322931{col 67}{space 3} 1.881092
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. svy: reg threat3 threat5 if treatment==0 
{txt}(running regress on estimation sample)
{res}
{txt}Survey: Linear regression

{col 1}Number of strata{col 20}= {res}        1{txt}{col 49}Number of obs{col 67}= {res}       533
{txt}{col 1}Number of PSUs{col 20}= {res}      533{txt}{col 49}Population size{col 67}={res} 533.879796
{txt}{col 49}Design df{col 67}= {res}       532
{txt}{col 49}F({res}   1{txt},{res}    532{txt}){col 67}= {res}     32.73
{txt}{col 49}Prob > F{col 67}= {res}    0.0000
{txt}{col 49}R-squared{col 67}= {res}    0.1339

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}  Linearized
{col 1}     threat3{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}threat5 {c |}{col 14}{res}{space 2} .4498292{col 26}{space 2} .0786235{col 37}{space 1}    5.72{col 46}{space 3}0.000{col 54}{space 4} .2953786{col 67}{space 3} .6042798
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 1.476521{col 26}{space 2} .2612639{col 37}{space 1}    5.65{col 46}{space 3}0.000{col 54}{space 4} .9632854{col 67}{space 3} 1.989756
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. svy: reg threat5 threat3 if treatment==0 
{txt}(running regress on estimation sample)
{res}
{txt}Survey: Linear regression

{col 1}Number of strata{col 20}= {res}        1{txt}{col 49}Number of obs{col 67}= {res}       533
{txt}{col 1}Number of PSUs{col 20}= {res}      533{txt}{col 49}Population size{col 67}={res} 533.879796
{txt}{col 49}Design df{col 67}= {res}       532
{txt}{col 49}F({res}   1{txt},{res}    532{txt}){col 67}= {res}     50.31
{txt}{col 49}Prob > F{col 67}= {res}    0.0000
{txt}{col 49}R-squared{col 67}= {res}    0.1339

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}  Linearized
{col 1}     threat5{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}threat3 {c |}{col 14}{res}{space 2} .2977206{col 26}{space 2} .0419762{col 37}{space 1}    7.09{col 46}{space 3}0.000{col 54}{space 4} .2152612{col 67}{space 3}   .38018
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 2.284723{col 26}{space 2} .1156882{col 37}{space 1}   19.75{col 46}{space 3}0.000{col 54}{space 4} 2.057461{col 67}{space 3} 2.511984
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. svy: reg threat4 threat5 if treatment==0 
{txt}(running regress on estimation sample)
{res}
{txt}Survey: Linear regression

{col 1}Number of strata{col 20}= {res}        1{txt}{col 49}Number of obs{col 67}= {res}       535
{txt}{col 1}Number of PSUs{col 20}= {res}      535{txt}{col 49}Population size{col 67}={res} 536.817939
{txt}{col 49}Design df{col 67}= {res}       534
{txt}{col 49}F({res}   1{txt},{res}    534{txt}){col 67}= {res}     11.75
{txt}{col 49}Prob > F{col 67}= {res}    0.0007
{txt}{col 49}R-squared{col 67}= {res}    0.0312

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}  Linearized
{col 1}     threat4{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}threat5 {c |}{col 14}{res}{space 2} .2358404{col 26}{space 2} .0688051{col 37}{space 1}    3.43{col 46}{space 3}0.001{col 54}{space 4} .1006784{col 67}{space 3} .3710024
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 2.310215{col 26}{space 2} .2212359{col 37}{space 1}   10.44{col 46}{space 3}0.000{col 54}{space 4} 1.875615{col 67}{space 3} 2.744814
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. svy: reg threat5 threat4 if treatment==0 
{txt}(running regress on estimation sample)
{res}
{txt}Survey: Linear regression

{col 1}Number of strata{col 20}= {res}        1{txt}{col 49}Number of obs{col 67}= {res}       535
{txt}{col 1}Number of PSUs{col 20}= {res}      535{txt}{col 49}Population size{col 67}={res} 536.817939
{txt}{col 49}Design df{col 67}= {res}       534
{txt}{col 49}F({res}   1{txt},{res}    534{txt}){col 67}= {res}     13.41
{txt}{col 49}Prob > F{col 67}= {res}    0.0003
{txt}{col 49}R-squared{col 67}= {res}    0.0312

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}  Linearized
{col 1}     threat5{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}threat4 {c |}{col 14}{res}{space 2} .1321456{col 26}{space 2}  .036082{col 37}{space 1}    3.66{col 46}{space 3}0.000{col 54}{space 4} .0612655{col 67}{space 3} .2030257
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 2.739686{col 26}{space 2} .1074362{col 37}{space 1}   25.50{col 46}{space 3}0.000{col 54}{space 4} 2.528636{col 67}{space 3} 2.950735
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. svy: reg threat1 threat2 if treatment==1 
{txt}(running regress on estimation sample)
{res}
{txt}Survey: Linear regression

{col 1}Number of strata{col 20}= {res}        1{txt}{col 49}Number of obs{col 67}= {res}       301
{txt}{col 1}Number of PSUs{col 20}= {res}      301{txt}{col 49}Population size{col 67}={res} 295.054756
{txt}{col 49}Design df{col 67}= {res}       300
{txt}{col 49}F({res}   1{txt},{res}    300{txt}){col 67}= {res}    113.93
{txt}{col 49}Prob > F{col 67}= {res}    0.0000
{txt}{col 49}R-squared{col 67}= {res}    0.3758

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}  Linearized
{col 1}     threat1{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}threat2 {c |}{col 14}{res}{space 2} .5945469{col 26}{space 2} .0557019{col 37}{space 1}   10.67{col 46}{space 3}0.000{col 54}{space 4} .4849311{col 67}{space 3} .7041628
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}  .789249{col 26}{space 2} .1385144{col 37}{space 1}    5.70{col 46}{space 3}0.000{col 54}{space 4}  .516666{col 67}{space 3} 1.061832
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. svy: reg threat2 threat1 if treatment==1 
{txt}(running regress on estimation sample)
{res}
{txt}Survey: Linear regression

{col 1}Number of strata{col 20}= {res}        1{txt}{col 49}Number of obs{col 67}= {res}       301
{txt}{col 1}Number of PSUs{col 20}= {res}      301{txt}{col 49}Population size{col 67}={res} 295.054756
{txt}{col 49}Design df{col 67}= {res}       300
{txt}{col 49}F({res}   1{txt},{res}    300{txt}){col 67}= {res}    149.04
{txt}{col 49}Prob > F{col 67}= {res}    0.0000
{txt}{col 49}R-squared{col 67}= {res}    0.3758

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}  Linearized
{col 1}     threat2{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}threat1 {c |}{col 14}{res}{space 2} .6320953{col 26}{space 2} .0517771{col 37}{space 1}   12.21{col 46}{space 3}0.000{col 54}{space 4} .5302029{col 67}{space 3} .7339877
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .9770508{col 26}{space 2} .1221644{col 37}{space 1}    8.00{col 46}{space 3}0.000{col 54}{space 4} .7366431{col 67}{space 3} 1.217458
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. svy: reg threat1 threat3 if treatment==1 
{txt}(running regress on estimation sample)
{res}
{txt}Survey: Linear regression

{col 1}Number of strata{col 20}= {res}        1{txt}{col 49}Number of obs{col 67}= {res}       310
{txt}{col 1}Number of PSUs{col 20}= {res}      310{txt}{col 49}Population size{col 67}={res} 306.849485
{txt}{col 49}Design df{col 67}= {res}       309
{txt}{col 49}F({res}   1{txt},{res}    309{txt}){col 67}= {res}    221.70
{txt}{col 49}Prob > F{col 67}= {res}    0.0000
{txt}{col 49}R-squared{col 67}= {res}    0.4812

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}  Linearized
{col 1}     threat1{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}threat3 {c |}{col 14}{res}{space 2} .6821434{col 26}{space 2} .0458135{col 37}{space 1}   14.89{col 46}{space 3}0.000{col 54}{space 4} .5919975{col 67}{space 3} .7722893
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .5046031{col 26}{space 2}  .109173{col 37}{space 1}    4.62{col 46}{space 3}0.000{col 54}{space 4} .2897865{col 67}{space 3} .7194197
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. svy: reg threat3 threat1 if treatment==1 
{txt}(running regress on estimation sample)
{res}
{txt}Survey: Linear regression

{col 1}Number of strata{col 20}= {res}        1{txt}{col 49}Number of obs{col 67}= {res}       310
{txt}{col 1}Number of PSUs{col 20}= {res}      310{txt}{col 49}Population size{col 67}={res} 306.849485
{txt}{col 49}Design df{col 67}= {res}       309
{txt}{col 49}F({res}   1{txt},{res}    309{txt}){col 67}= {res}    244.07
{txt}{col 49}Prob > F{col 67}= {res}    0.0000
{txt}{col 49}R-squared{col 67}= {res}    0.4812

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}  Linearized
{col 1}     threat3{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}threat1 {c |}{col 14}{res}{space 2} .7053884{col 26}{space 2} .0451518{col 37}{space 1}   15.62{col 46}{space 3}0.000{col 54}{space 4} .6165446{col 67}{space 3} .7942322
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .9468721{col 26}{space 2} .1156355{col 37}{space 1}    8.19{col 46}{space 3}0.000{col 54}{space 4} .7193396{col 67}{space 3} 1.174405
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. svy: reg threat1 threat4 if treatment==1 
{txt}(running regress on estimation sample)
{res}
{txt}Survey: Linear regression

{col 1}Number of strata{col 20}= {res}        1{txt}{col 49}Number of obs{col 67}= {res}       311
{txt}{col 1}Number of PSUs{col 20}= {res}      311{txt}{col 49}Population size{col 67}={res} 307.307914
{txt}{col 49}Design df{col 67}= {res}       310
{txt}{col 49}F({res}   1{txt},{res}    310{txt}){col 67}= {res}    169.28
{txt}{col 49}Prob > F{col 67}= {res}    0.0000
{txt}{col 49}R-squared{col 67}= {res}    0.3697

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}  Linearized
{col 1}     threat1{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}threat4 {c |}{col 14}{res}{space 2} .5518061{col 26}{space 2} .0424117{col 37}{space 1}   13.01{col 46}{space 3}0.000{col 54}{space 4} .4683549{col 67}{space 3} .6352574
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .6703462{col 26}{space 2} .1066584{col 37}{space 1}    6.28{col 46}{space 3}0.000{col 54}{space 4} .4604802{col 67}{space 3} .8802122
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. svy: reg threat4 threat1 if treatment==1 
{txt}(running regress on estimation sample)
{res}
{txt}Survey: Linear regression

{col 1}Number of strata{col 20}= {res}        1{txt}{col 49}Number of obs{col 67}= {res}       311
{txt}{col 1}Number of PSUs{col 20}= {res}      311{txt}{col 49}Population size{col 67}={res} 307.307914
{txt}{col 49}Design df{col 67}= {res}       310
{txt}{col 49}F({res}   1{txt},{res}    310{txt}){col 67}= {res}    214.66
{txt}{col 49}Prob > F{col 67}= {res}    0.0000
{txt}{col 49}R-squared{col 67}= {res}    0.3697

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}  Linearized
{col 1}     threat4{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}threat1 {c |}{col 14}{res}{space 2} .6699736{col 26}{space 2} .0457278{col 37}{space 1}   14.65{col 46}{space 3}0.000{col 54}{space 4} .5799975{col 67}{space 3} .7599497
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 1.318839{col 26}{space 2} .1379183{col 37}{space 1}    9.56{col 46}{space 3}0.000{col 54}{space 4} 1.047465{col 67}{space 3} 1.590213
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. svy: reg threat1 threat5 if treatment==1 
{txt}(running regress on estimation sample)
{res}
{txt}Survey: Linear regression

{col 1}Number of strata{col 20}= {res}        1{txt}{col 49}Number of obs{col 67}= {res}       303
{txt}{col 1}Number of PSUs{col 20}= {res}      303{txt}{col 49}Population size{col 67}={res}  299.79151
{txt}{col 49}Design df{col 67}= {res}       302
{txt}{col 49}F({res}   1{txt},{res}    302{txt}){col 67}= {res}    201.34
{txt}{col 49}Prob > F{col 67}= {res}    0.0000
{txt}{col 49}R-squared{col 67}= {res}    0.4296

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}  Linearized
{col 1}     threat1{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}threat5 {c |}{col 14}{res}{space 2} .6333534{col 26}{space 2} .0446359{col 37}{space 1}   14.19{col 46}{space 3}0.000{col 54}{space 4} .5455166{col 67}{space 3} .7211902
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .5514287{col 26}{space 2}  .105023{col 37}{space 1}    5.25{col 46}{space 3}0.000{col 54}{space 4} .3447591{col 67}{space 3} .7580983
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. svy: reg threat5 threat1 if treatment==1 
{txt}(running regress on estimation sample)
{res}
{txt}Survey: Linear regression

{col 1}Number of strata{col 20}= {res}        1{txt}{col 49}Number of obs{col 67}= {res}       303
{txt}{col 1}Number of PSUs{col 20}= {res}      303{txt}{col 49}Population size{col 67}={res}  299.79151
{txt}{col 49}Design df{col 67}= {res}       302
{txt}{col 49}F({res}   1{txt},{res}    302{txt}){col 67}= {res}    280.82
{txt}{col 49}Prob > F{col 67}= {res}    0.0000
{txt}{col 49}R-squared{col 67}= {res}    0.4296

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}  Linearized
{col 1}     threat5{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}threat1 {c |}{col 14}{res}{space 2} .6782583{col 26}{space 2} .0404748{col 37}{space 1}   16.76{col 46}{space 3}0.000{col 54}{space 4} .5986101{col 67}{space 3} .7579066
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 1.115537{col 26}{space 2} .1153127{col 37}{space 1}    9.67{col 46}{space 3}0.000{col 54}{space 4} .8886188{col 67}{space 3} 1.342455
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. svy: reg threat2 threat3 if treatment==1 
{txt}(running regress on estimation sample)
{res}
{txt}Survey: Linear regression

{col 1}Number of strata{col 20}= {res}        1{txt}{col 49}Number of obs{col 67}= {res}       300
{txt}{col 1}Number of PSUs{col 20}= {res}      300{txt}{col 49}Population size{col 67}={res} 299.092246
{txt}{col 49}Design df{col 67}= {res}       299
{txt}{col 49}F({res}   1{txt},{res}    299{txt}){col 67}= {res}    230.86
{txt}{col 49}Prob > F{col 67}= {res}    0.0000
{txt}{col 49}R-squared{col 67}= {res}    0.4438

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}  Linearized
{col 1}     threat2{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}threat3 {c |}{col 14}{res}{space 2} .6776992{col 26}{space 2} .0446025{col 37}{space 1}   15.19{col 46}{space 3}0.000{col 54}{space 4} .5899246{col 67}{space 3} .7654738
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .6832156{col 26}{space 2}   .11849{col 37}{space 1}    5.77{col 46}{space 3}0.000{col 54}{space 4} .4500355{col 67}{space 3} .9163956
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. svy: reg threat3 threat2 if treatment==1 
{txt}(running regress on estimation sample)
{res}
{txt}Survey: Linear regression

{col 1}Number of strata{col 20}= {res}        1{txt}{col 49}Number of obs{col 67}= {res}       300
{txt}{col 1}Number of PSUs{col 20}= {res}      300{txt}{col 49}Population size{col 67}={res} 299.092246
{txt}{col 49}Design df{col 67}= {res}       299
{txt}{col 49}F({res}   1{txt},{res}    299{txt}){col 67}= {res}    207.36
{txt}{col 49}Prob > F{col 67}= {res}    0.0000
{txt}{col 49}R-squared{col 67}= {res}    0.4438

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}  Linearized
{col 1}     threat3{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}threat2 {c |}{col 14}{res}{space 2}  .654795{col 26}{space 2} .0454718{col 37}{space 1}   14.40{col 46}{space 3}0.000{col 54}{space 4} .5653098{col 67}{space 3} .7442803
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .9474916{col 26}{space 2} .1201857{col 37}{space 1}    7.88{col 46}{space 3}0.000{col 54}{space 4} .7109746{col 67}{space 3} 1.184009
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. svy: reg threat2 threat4 if treatment==1 
{txt}(running regress on estimation sample)
{res}
{txt}Survey: Linear regression

{col 1}Number of strata{col 20}= {res}        1{txt}{col 49}Number of obs{col 67}= {res}       304
{txt}{col 1}Number of PSUs{col 20}= {res}      304{txt}{col 49}Population size{col 67}={res} 303.975974
{txt}{col 49}Design df{col 67}= {res}       303
{txt}{col 49}F({res}   1{txt},{res}    303{txt}){col 67}= {res}    180.85
{txt}{col 49}Prob > F{col 67}= {res}    0.0000
{txt}{col 49}R-squared{col 67}= {res}    0.4290

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}  Linearized
{col 1}     threat2{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}threat4 {c |}{col 14}{res}{space 2} .6147178{col 26}{space 2} .0457107{col 37}{space 1}   13.45{col 46}{space 3}0.000{col 54}{space 4} .5247672{col 67}{space 3} .7046683
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .6481693{col 26}{space 2} .1341068{col 37}{space 1}    4.83{col 46}{space 3}0.000{col 54}{space 4} .3842706{col 67}{space 3}  .912068
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. svy: reg threat4 threat2 if treatment==1 
{txt}(running regress on estimation sample)
{res}
{txt}Survey: Linear regression

{col 1}Number of strata{col 20}= {res}        1{txt}{col 49}Number of obs{col 67}= {res}       304
{txt}{col 1}Number of PSUs{col 20}= {res}      304{txt}{col 49}Population size{col 67}={res} 303.975974
{txt}{col 49}Design df{col 67}= {res}       303
{txt}{col 49}F({res}   1{txt},{res}    303{txt}){col 67}= {res}    222.42
{txt}{col 49}Prob > F{col 67}= {res}    0.0000
{txt}{col 49}R-squared{col 67}= {res}    0.4290

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}  Linearized
{col 1}     threat4{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}threat2 {c |}{col 14}{res}{space 2} .6979483{col 26}{space 2} .0467987{col 37}{space 1}   14.91{col 46}{space 3}0.000{col 54}{space 4} .6058566{col 67}{space 3}   .79004
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 1.157618{col 26}{space 2} .1392555{col 37}{space 1}    8.31{col 46}{space 3}0.000{col 54}{space 4} .8835881{col 67}{space 3} 1.431649
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. svy: reg threat2 threat5 if treatment==1 
{txt}(running regress on estimation sample)
{res}
{txt}Survey: Linear regression

{col 1}Number of strata{col 20}= {res}        1{txt}{col 49}Number of obs{col 67}= {res}       301
{txt}{col 1}Number of PSUs{col 20}= {res}      301{txt}{col 49}Population size{col 67}={res} 301.459571
{txt}{col 49}Design df{col 67}= {res}       300
{txt}{col 49}F({res}   1{txt},{res}    300{txt}){col 67}= {res}    386.84
{txt}{col 49}Prob > F{col 67}= {res}    0.0000
{txt}{col 49}R-squared{col 67}= {res}    0.5891

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}  Linearized
{col 1}     threat2{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}threat5 {c |}{col 14}{res}{space 2} .7600159{col 26}{space 2} .0386417{col 37}{space 1}   19.67{col 46}{space 3}0.000{col 54}{space 4} .6839728{col 67}{space 3} .8360591
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .3799866{col 26}{space 2} .0956467{col 37}{space 1}    3.97{col 46}{space 3}0.000{col 54}{space 4} .1917631{col 67}{space 3} .5682101
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. svy: reg threat5 threat2 if treatment==1 
{txt}(running regress on estimation sample)
{res}
{txt}Survey: Linear regression

{col 1}Number of strata{col 20}= {res}        1{txt}{col 49}Number of obs{col 67}= {res}       301
{txt}{col 1}Number of PSUs{col 20}= {res}      301{txt}{col 49}Population size{col 67}={res} 301.459571
{txt}{col 49}Design df{col 67}= {res}       300
{txt}{col 49}F({res}   1{txt},{res}    300{txt}){col 67}= {res}    356.20
{txt}{col 49}Prob > F{col 67}= {res}    0.0000
{txt}{col 49}R-squared{col 67}= {res}    0.5891

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}  Linearized
{col 1}     threat5{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}threat2 {c |}{col 14}{res}{space 2} .7751406{col 26}{space 2} .0410706{col 37}{space 1}   18.87{col 46}{space 3}0.000{col 54}{space 4} .6943177{col 67}{space 3} .8559636
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .7862685{col 26}{space 2} .1239231{col 37}{space 1}    6.34{col 46}{space 3}0.000{col 54}{space 4} .5423998{col 67}{space 3} 1.030137
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. svy: reg threat3 threat4 if treatment==1 
{txt}(running regress on estimation sample)
{res}
{txt}Survey: Linear regression

{col 1}Number of strata{col 20}= {res}        1{txt}{col 49}Number of obs{col 67}= {res}       310
{txt}{col 1}Number of PSUs{col 20}= {res}      310{txt}{col 49}Population size{col 67}={res} 311.345403
{txt}{col 49}Design df{col 67}= {res}       309
{txt}{col 49}F({res}   1{txt},{res}    309{txt}){col 67}= {res}    305.42
{txt}{col 49}Prob > F{col 67}= {res}    0.0000
{txt}{col 49}R-squared{col 67}= {res}    0.5014

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}  Linearized
{col 1}     threat3{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}threat4 {c |}{col 14}{res}{space 2} .6561819{col 26}{space 2}  .037547{col 37}{space 1}   17.48{col 46}{space 3}0.000{col 54}{space 4} .5823018{col 67}{space 3}  .730062
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .6775559{col 26}{space 2} .1041528{col 37}{space 1}    6.51{col 46}{space 3}0.000{col 54}{space 4} .4726174{col 67}{space 3} .8824944
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. svy: reg threat4 threat3 if treatment==1 
{txt}(running regress on estimation sample)
{res}
{txt}Survey: Linear regression

{col 1}Number of strata{col 20}= {res}        1{txt}{col 49}Number of obs{col 67}= {res}       310
{txt}{col 1}Number of PSUs{col 20}= {res}      310{txt}{col 49}Population size{col 67}={res} 311.345403
{txt}{col 49}Design df{col 67}= {res}       309
{txt}{col 49}F({res}   1{txt},{res}    309{txt}){col 67}= {res}    327.33
{txt}{col 49}Prob > F{col 67}= {res}    0.0000
{txt}{col 49}R-squared{col 67}= {res}    0.5014

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}  Linearized
{col 1}     threat4{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}threat3 {c |}{col 14}{res}{space 2} .7641532{col 26}{space 2} .0422364{col 37}{space 1}   18.09{col 46}{space 3}0.000{col 54}{space 4} .6810458{col 67}{space 3} .8472606
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .8910225{col 26}{space 2} .1341869{col 37}{space 1}    6.64{col 46}{space 3}0.000{col 54}{space 4} .6269868{col 67}{space 3} 1.155058
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. svy: reg threat3 threat5 if treatment==1 
{txt}(running regress on estimation sample)
{res}
{txt}Survey: Linear regression

{col 1}Number of strata{col 20}= {res}        1{txt}{col 49}Number of obs{col 67}= {res}       306
{txt}{col 1}Number of PSUs{col 20}= {res}      306{txt}{col 49}Population size{col 67}={res} 307.147617
{txt}{col 49}Design df{col 67}= {res}       305
{txt}{col 49}F({res}   1{txt},{res}    305{txt}){col 67}= {res}    276.05
{txt}{col 49}Prob > F{col 67}= {res}    0.0000
{txt}{col 49}R-squared{col 67}= {res}    0.4952

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}  Linearized
{col 1}     threat3{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}threat5 {c |}{col 14}{res}{space 2} .6904325{col 26}{space 2} .0415555{col 37}{space 1}   16.61{col 46}{space 3}0.000{col 54}{space 4} .6086607{col 67}{space 3} .7722043
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .7018467{col 26}{space 2} .1078468{col 37}{space 1}    6.51{col 46}{space 3}0.000{col 54}{space 4} .4896289{col 67}{space 3} .9140646
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. svy: reg threat5 threat3 if treatment==1 
{txt}(running regress on estimation sample)
{res}
{txt}Survey: Linear regression

{col 1}Number of strata{col 20}= {res}        1{txt}{col 49}Number of obs{col 67}= {res}       306
{txt}{col 1}Number of PSUs{col 20}= {res}      306{txt}{col 49}Population size{col 67}={res} 307.147617
{txt}{col 49}Design df{col 67}= {res}       305
{txt}{col 49}F({res}   1{txt},{res}    305{txt}){col 67}= {res}    281.90
{txt}{col 49}Prob > F{col 67}= {res}    0.0000
{txt}{col 49}R-squared{col 67}= {res}    0.4952

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}  Linearized
{col 1}     threat5{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}threat3 {c |}{col 14}{res}{space 2} .7171976{col 26}{space 2} .0427161{col 37}{space 1}   16.79{col 46}{space 3}0.000{col 54}{space 4} .6331419{col 67}{space 3} .8012532
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .8243369{col 26}{space 2} .1250875{col 37}{space 1}    6.59{col 46}{space 3}0.000{col 54}{space 4} .5781933{col 67}{space 3} 1.070481
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. svy: reg threat4 threat5 if treatment==1 
{txt}(running regress on estimation sample)
{res}
{txt}Survey: Linear regression

{col 1}Number of strata{col 20}= {res}        1{txt}{col 49}Number of obs{col 67}= {res}       308
{txt}{col 1}Number of PSUs{col 20}= {res}      308{txt}{col 49}Population size{col 67}={res} 310.467976
{txt}{col 49}Design df{col 67}= {res}       307
{txt}{col 49}F({res}   1{txt},{res}    307{txt}){col 67}= {res}    618.96
{txt}{col 49}Prob > F{col 67}= {res}    0.0000
{txt}{col 49}R-squared{col 67}= {res}    0.6197

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}  Linearized
{col 1}     threat4{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}threat5 {c |}{col 14}{res}{space 2} .8392047{col 26}{space 2} .0337317{col 37}{space 1}   24.88{col 46}{space 3}0.000{col 54}{space 4} .7728301{col 67}{space 3} .9055793
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .6073287{col 26}{space 2}  .108635{col 37}{space 1}    5.59{col 46}{space 3}0.000{col 54}{space 4} .3935652{col 67}{space 3} .8210921
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. svy: reg threat5 threat4 if treatment==1
{txt}(running regress on estimation sample)
{res}
{txt}Survey: Linear regression

{col 1}Number of strata{col 20}= {res}        1{txt}{col 49}Number of obs{col 67}= {res}       308
{txt}{col 1}Number of PSUs{col 20}= {res}      308{txt}{col 49}Population size{col 67}={res} 310.467976
{txt}{col 49}Design df{col 67}= {res}       307
{txt}{col 49}F({res}   1{txt},{res}    307{txt}){col 67}= {res}    343.98
{txt}{col 49}Prob > F{col 67}= {res}    0.0000
{txt}{col 49}R-squared{col 67}= {res}    0.6197

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}  Linearized
{col 1}     threat5{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}threat4 {c |}{col 14}{res}{space 2}   .73838{col 26}{space 2} .0398118{col 37}{space 1}   18.55{col 46}{space 3}0.000{col 54}{space 4} .6600416{col 67}{space 3} .8167185
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .5574115{col 26}{space 2} .1231388{col 37}{space 1}    4.53{col 46}{space 3}0.000{col 54}{space 4} .3151087{col 67}{space 3} .7997144
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. svyset, clear
{txt}
{com}. 
. 
. *********************************************************************
. * MULTIPLE IMPUTATION
. *********************************************************************
. 
. * impute (use recoded var in which missing (often code 5) is set to missing "." 
. * only exception is Work_status as there is more info in original variable
. 
. set seed 974302623
{txt}
{com}. mi set mlong
{txt}
{com}. mi register imputed auth1 auth2 auth3 est1 est2 est3 est4 est5 GHbb1 GHbb2 GHbb3 GHbb4 GHbb5 GHbb6 GHbb7 GHbb8 GHmu1 GHmu2 GHmu3 GHmu4 GHmu5 GHmu6 GHmu7 GHmu8 GHee1 GHee2 GHee3 GHee4 GHee5 GHee6 GHee7 GHee8 GHwb1 GHwb2 GHwb3 GHwb4 GHwb5 GHwb6 GHwb7 GHwb8 SDbb1 SDbb2 SDbb3 SDmu1 SDmu2 SDmu3 SDee1 SDee2 SDee3
{res}{txt}{p}
(851 {it:m}=0 obs. now marked as incomplete)
{p_end}

{com}. mi impute mvn auth1 auth2 auth3 est1 est2 est3 est4 est5 GHbb1 GHbb2 GHbb3 GHbb4 GHbb5 GHbb6 GHbb7 GHbb8 GHmu1 GHmu2 GHmu3 GHmu4 GHmu5 GHmu6 GHmu7 GHmu8 GHee1 GHee2 GHee3 GHee4 GHee5 GHee6 GHee7 GHee8 GHwb1 GHwb2 GHwb3 GHwb4 GHwb5 GHwb6 GHwb7 GHwb8 SDbb1 SDbb2 SDbb3 SDmu1 SDmu2 SDmu3 SDee1 SDee2 SDee3 = female Age edu_age i.SocialGrade i.Work_status UKborn i.threat1 i.threat2 i.threat3 i.threat4 i.threat5 i.threat6 i.threat7 retrofin retroecon prosfin prosecon Bid1 Bid2 Bid3 Bid4 treatment, add(10) force initmcmc(em, iterate(400))
{res}
{txt}Performing EM optimization:
{txt}  observed log likelihood = {res} 1774.4701{txt} at iteration 308
{res}
{txt}Performing MCMC data augmentation ... 
{res}{txt}
Multivariate imputation{txt}{col 45}{ralign 12:Imputations }= {res}      10
{txt}Multivariate normal regression{txt}{col 45}{ralign 12:added }= {res}      10
{txt}Imputed: {it:m}=1 through {it:m}=10{txt}{col 45}{ralign 12:updated }= {res}       0

{txt}Prior: uniform{txt}{col 45}{ralign 12:Iterations }= {res}    1000
{txt}{col 45}{ralign 12:burn-in }= {res}     100
{txt}{col 45}{ralign 12:between }= {res}     100

{txt}{hline 19}{c TT}{hline 35}{hline 11}
{txt}{col 20}{c |}{center 46:  Observations per {it:m}}
{txt}{col 20}{c LT}{hline 35}{c TT}{hline 10}
{txt}{col 11}Variable {c |}{ralign 12:Complete }{ralign 13:Incomplete }{ralign 10:Imputed }{c |}{ralign 10:Total}
{hline 19}{c +}{hline 35}{c +}{hline 10}
{txt}{ralign 19:auth1 }{c |}{res}        838           91        27 {txt}{c |}{res}       929
{txt}{ralign 19:auth2 }{c |}{res}        851           78         9 {txt}{c |}{res}       929
{txt}{ralign 19:auth3 }{c |}{res}        830           99        26 {txt}{c |}{res}       929
{txt}{ralign 19:est1 }{c |}{res}        845           84        27 {txt}{c |}{res}       929
{txt}{ralign 19:est2 }{c |}{res}        789          140        52 {txt}{c |}{res}       929
{txt}{ralign 19:est3 }{c |}{res}        859           70        17 {txt}{c |}{res}       929
{txt}{ralign 19:est4 }{c |}{res}        763          166        65 {txt}{c |}{res}       929
{txt}{ralign 19:est5 }{c |}{res}        850           79        20 {txt}{c |}{res}       929
{txt}{ralign 19:GHbb1 }{c |}{res}        677          252       106 {txt}{c |}{res}       929
{txt}{ralign 19:GHbb2 }{c |}{res}        703          226        86 {txt}{c |}{res}       929
{txt}{ralign 19:GHbb3 }{c |}{res}        703          226        90 {txt}{c |}{res}       929
{txt}{ralign 19:GHbb4 }{c |}{res}        696          233        94 {txt}{c |}{res}       929
{txt}{ralign 19:GHbb5 }{c |}{res}        712          217        88 {txt}{c |}{res}       929
{txt}{ralign 19:GHbb6 }{c |}{res}        719          210        82 {txt}{c |}{res}       929
{txt}{ralign 19:GHbb7 }{c |}{res}        706          223        90 {txt}{c |}{res}       929
{txt}{ralign 19:GHbb8 }{c |}{res}        756          173        61 {txt}{c |}{res}       929
{txt}{ralign 19:GHmu1 }{c |}{res}        684          245       109 {txt}{c |}{res}       929
{txt}{ralign 19:GHmu2 }{c |}{res}        725          204        78 {txt}{c |}{res}       929
{txt}{ralign 19:GHmu3 }{c |}{res}        712          217        87 {txt}{c |}{res}       929
{txt}{ralign 19:GHmu4 }{c |}{res}        690          239        94 {txt}{c |}{res}       929
{txt}{ralign 19:GHmu5 }{c |}{res}        695          234        96 {txt}{c |}{res}       929
{txt}{ralign 19:GHmu6 }{c |}{res}        722          207        78 {txt}{c |}{res}       929
{txt}{ralign 19:GHmu7 }{c |}{res}        712          217        84 {txt}{c |}{res}       929
{txt}{ralign 19:GHmu8 }{c |}{res}        746          183        72 {txt}{c |}{res}       929
{txt}{ralign 19:GHee1 }{c |}{res}        650          279       119 {txt}{c |}{res}       929
{txt}{ralign 19:GHee2 }{c |}{res}        647          282       119 {txt}{c |}{res}       929
{txt}{ralign 19:GHee3 }{c |}{res}        651          278       120 {txt}{c |}{res}       929
{txt}{ralign 19:GHee4 }{c |}{res}        671          258       110 {txt}{c |}{res}       929
{txt}{ralign 19:GHee5 }{c |}{res}        715          214        88 {txt}{c |}{res}       929
{txt}{ralign 19:GHee6 }{c |}{res}        670          259       103 {txt}{c |}{res}       929
{txt}{ralign 19:GHee7 }{c |}{res}        677          252       108 {txt}{c |}{res}       929
{txt}{ralign 19:GHee8 }{c |}{res}        735          194        80 {txt}{c |}{res}       929
{txt}{ralign 19:GHwb1 }{c |}{res}        908           21        16 {txt}{c |}{res}       929
{txt}{ralign 19:GHwb2 }{c |}{res}        797          132        94 {txt}{c |}{res}       929
{txt}{ralign 19:GHwb3 }{c |}{res}        909           20        17 {txt}{c |}{res}       929
{txt}{ralign 19:GHwb4 }{c |}{res}        710          219       153 {txt}{c |}{res}       929
{txt}{ralign 19:GHwb5 }{c |}{res}        806          123        88 {txt}{c |}{res}       929
{txt}{ralign 19:GHwb6 }{c |}{res}        780          149       109 {txt}{c |}{res}       929
{txt}{ralign 19:GHwb7 }{c |}{res}        804          125        91 {txt}{c |}{res}       929
{txt}{ralign 19:GHwb8 }{c |}{res}        506          423       286 {txt}{c |}{res}       929
{txt}{ralign 19:SDbb1 }{c |}{res}        593          336       162 {txt}{c |}{res}       929
{txt}{ralign 19:SDbb2 }{c |}{res}        551          378       190 {txt}{c |}{res}       929
{txt}{ralign 19:SDbb3 }{c |}{res}        564          365       179 {txt}{c |}{res}       929
{txt}{ralign 19:SDmu1 }{c |}{res}        614          315       147 {txt}{c |}{res}       929
{txt}{ralign 19:SDmu2 }{c |}{res}        578          351       173 {txt}{c |}{res}       929
{txt}{ralign 19:SDmu3 }{c |}{res}        609          320       158 {txt}{c |}{res}       929
{txt}{ralign 19:SDee1 }{c |}{res}        607          322       157 {txt}{c |}{res}       929
{txt}{ralign 19:SDee2 }{c |}{res}        570          359       174 {txt}{c |}{res}       929
{txt}{ralign 19:SDee3 }{c |}{res}        570          359       174 {txt}{c |}{res}       929
{txt}{hline 19}{c BT}{hline 35}{c BT}{hline 10}
{p 0 1 1 66}(complete + incomplete = total; imputed is the minimum across {it:m}
 of the number of filled-in observations.){p_end}

{p 0 6 6 71}Note: Right-hand-side variables (or weights) have missing values; model parameters estimated using listwise deletion.{p_end}

{com}. display c(seed)
{res}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
{txt}
{com}. /* state of random-number generator is: 
> XAA9652417f36b6e8a56a545688a3c265d3f6191fbb5ab1b057978c86d92df0d9cbaadb6c90381cbd4ea26f2948b718b1c54639426
> > 585e6b4254f6a77f540ed548d27e0a28cb6d93c7114d31afaec8de1088dac78b359463bbb39675a332ad7c603debcc3ba3b3eecf
> > 1be2faf6b33278fc5775adc65c9b0682dbf82e7849b13670273ed51b92add4ec8bdace9fbbb04847cd780164ab60b7e0fd812f0d
> > 3c4e916ed5b9549092ca9002226ce63cf7f39c89a17f9a0559e5a494bf02f6490728fa558e8af97ee3193d6f17d7ba60698cf64e
> > af0ab5b942e03f2f0bda130099c68f10167f088e581e6df7106d11196b6e23d54e5d9ac4915194cf1f3d12a91505c0121fb95bc4
> > 6445440ce504dba35058e262cb9ee34ef2f8509d38bd41b47db459f3978fe145a6254a35e1552496b99be36836b2f0c20a65a7c8
> > ecebfdb117fef5aa1179c61a4e0efe1e8353138f55968bbd72b599ef427ada333e217ae9ba8ebccbf79a224b0132dd11a18ab214
> > a7a0e3e30a86e708277f24028f38ff01f9daa90416f9352f82f5fefda4a856b735012b9cb1e9a77e38b1c9b4cbcaf900f368d3c2
> > ff234d89648348276cbdd6ec265ba98a9790c9b2cdbf2b68c0dc2a502e35b980957e6db2794446e81e80b991a5ea6573cd83b0f6
> > 5cad807307626039b82399c7aea1280dca9e4d255cc660d0ed1b828b94c7cb4340056d178effa8b2e75401960bd04cd904115131
> > dff6e83e3fcfee390c26c96587d373d399ce8ffbd95334638b424512600e047b09a0cd80812cb1c77b52e150904bcaf07a2e442b
> > 5382358131961afb9753905df035ced664915e3ba786927e7471d330d73b7f8ee7afbc00cf9ad64a2de7950f38e35ac9e1c9c289
> > 8c816a2accde4524497de0936dabc3ee35eb593f5e9a5d04264512e3c6090c0ae4f85c5d9dbd03e86c5af19a32a512e9605360c2
> > 2823b41983ddbbe66daab744cea988d7b37b8f59f70e6e2b909567fc6d7ef5c6512f770b039f263b6f53702ef36fca42d8f0a950
> > 8b50eb62c03793c563e9803a0f7d8b41c70cb6e18f3ff761913ae84010a47e15e99f444eed85a5d6003a7a8c09f8480ffb3ffc86
> > 2634150a0c0ac7ba29088a2a31c16521bf04c402604362eda3eaba97154416d31c6522a8b7ea818b098306c3aff3061dba0e08fe
> > 0d85ea701885aa46d26e9bd7ff81435d2a3a024929d188272e35b3835afa018cc1f9f75d29fd30987145e6c9a75bfb756dc1d19e
> > 366f6559ff806f19ccd2cdc8a986fc10662619e06b476ba956ac92cff38876432a3081718687fcacbbc026b629ed0f38b2db4e05
> > 2435a2c92dea3230be8804785629c4a4faa3dadd10355ecd1945ba83c20c819e34028fa4356b1fa43218202c6bf7af46f9f32f2a
> > ec81579e4c44439e72db00642fea05bd5230d795326714b8974fe33c3638183fe20a467bbb285fd63d5a24311b17a4d49bc71da6
> > b5a130730ccbcabeac12d86b5be1b426366bddf341777717d129e713c9056ed58d75050ef4b0e9156ac2dd527b42a4c24a3ef458
> > 096848bedd4d06b7095a9b141b148d19a81689fb64031d1c9ee476218289bbfac6ae59329f11a540711fd1c7c1cc0a48f60d6898
> > e2a83de824760478ba2300ec059c569715b0922984a7950008ea093a895a0cfa53b736874fdb45d51b42110ebcff0d6a7f0a3f45
> > b4e1f7daab227fd71eb7669306949139dc53b63c55f868b76d47f5f57da044abc64c533936e70e9ed8cbcf70a33f2e9de1112712
> > 7d9a73df3bfb83b2a2e741add72832143d1e399967dea03658e1b29f9e277efad4577394bb117374010f9e3e07da40c46b5f381f
> > 13aa89f58242a17ff05579c209c902315394856d0340e4a34063fb1272511b240a07eea3864adbe70815996f849ac1f94156487c
> > cbb950274506f6af1032767b1a2b011fa2923683587ba2ae76d33ca82bee4a097d06bdd0dff2d418bca27209445249af6976104c
> > 7e7dd28ed40ccbae40bd5ce40a539acc95ae91714e1f71a3093b6880ae8bd7cf1f4e359dc8d71fed8b875d80a634cde3d73853c1
> > ceafd8fd88a9cda2a2fd99f6f476b0084617e9038f7941ae12a8fc25548964e72663f327a13933bc6709127297d87c56ef81bed4
> > e15d9b49681278da02b877280a2b6b8d5e0b934717f93caab5cb0629e8d9079dfcc39fff49ec3f2820b81d97f7a9d632ca845607
> > 7b8012b8b6959e15d37c6064f3801685565219de5737c7a7707c5efacc5f8f4e85ce8acbb0e44b422868f1bbb56ca5b25e67c73b
> > 4241f357535424a9d07dca5806d165c0f6a78eb826b975af3e29cca7322dfb6fb7250f7e42f79950c85a7c34c6b1cbafa9c8871b
> > 8bf0dc4a9058ba554a14b9ff3bde8a926edef326592b573c3435de45599c6cbbed208c0b94aab83a708643c568d28061f35358cc
> > bf78ac9f3469357d763f966e63e11179bfe3e36d24101d68a9b1c10894959c703b32c050fcfa5980f27c178dafb64de081e7098b
> > 29a904ec8cc61723bc7dbb05fb5e5c09a421ac7cd0ef394bebb2c42930b041537e1b56beb2b23dd47a2b24e3dad668afbeffea48
> > f34d36327208136a71b12f5f7e64ccc70c3a3b240375b601a37a0abcd48f059a29a66456eee37e31f4e7af9ab4e0f41e048a2f41
> > 17a735c38fb23cb1d19ea4e76fda5a51d22a5b30f09e9a93ec806e9d3d13ccae3ce9bd4eee1eb9aee6913cace67532e19ca046ae
> > 0004a587f40e88c92ad0de146476e448e4b5452dd794092587b532983e4bd2b9c6206a61290b94f4950e4d5315795625b8efff45
> > 3a9e3e1d3d3a6450ea038574b84c9ed597fba69115781a0816fe457ac7c63fab08e8991e12a7823d4fd36e1f895e5aa4f45ca102
> > 71d0e338908948dce443c323fc7ed5175c07971e5cd6767981a9c3da2c4f7e2404ecb7c8f6c2c6e5a8a2107e8395e5a9325fd816
> > 0dc62d5c232bf3d80c94df393980af11a69815f55fc15e011748e10f5d34dbd3aa2d63d96d6db38849025865450835d5d75b9274
> > bf32ccba3f7d28c5d1311c9d25ed00e9dbf63e1f07428aa141f08ed0814b3d0e1246fa23174f8bdaaf4a428a3a141054cd4f1376
> > da973294632a58250ca0e8008df72e0fcfad429f4297ea56345f88386b3571c3ed1548c025df7f2daf4b41f5281a161374c6dffc
> > 28e460eb11c057c6fdc46fa319089a42fd98ab837424ad353fdc0fa14654e1ede5c235baa6c62da982031c6f23e39956b4baafc6
> > 2357ca5a99c2342096c3f5ceebd51ce178e34fcbf1a31998ce5c04895bebb19f2d9c72887fcb045c42336dce3c26efe42ba29ca3
> > f404541b3a5d369fdfb7438cfa699546e480c4b5f7681a6274368cbd35b3b45cf6d082f916dfdc7338da0ae5f806b364ddc4ca32
> > f3ec61347def241159a77bc505fc08c3a80ded345a6506a7fb340505cfc1411fdfc23f1ae9a4b48a7d85bc9d7beae4063321ac03
> > 8538ad895081b6d1a3b499b7163ca90008c0d66562bf94386e60f4eaaf66df5895463344115c33efbe43e00b5c6260b66632f1c9
> > c0001000000c845c0
> */
. 
. save "W1 imputed.dta"
{txt}file W1 imputed.dta saved

{com}. 
. 
. *********************************************************************
. * FURTHER RECODES AND DESCRIPTIVES
. *********************************************************************
. 
. * work status (already 31 missing in original code (coded with missing value code .a)
. recode Work_status (1=1) (2/3 =2) (4=3) (5=4) (6=5) (7/8 = 6), into(work_status)
{txt}(4348 differences between Work_status and work_status)

{com}. label value work_status work_status
{txt}
{com}. label var work_status "working status"
{txt}
{com}. 
. * British identity - 2 versions
. gen Bidentity = (Bid1 + Bid2 + Bid3 + Bid4)/4
{txt}(1,332 missing values generated)

{com}. ** excludes all respondents with 1 or more missing
. egen Bidentity_2 = rowmean(Bid1-Bid4)
{txt}(242 missing values generated)

{com}. ** takes average over valid items, only excludes those with 4 missing
. sum Bidentity Bidentity_2

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 3}Bidentity {c |}{res}      8,107    3.177347    .6013783          1          4
{txt}{space 1}Bidentity_2 {c |}{res}      9,197    3.134872    .6270815          1          4
{txt}
{com}. ** lower mean on _2
. 
. * authoritarian values, self-esteem and social distance
. gen authvalues = (auth1+ auth2+ auth3)/3 
{txt}(1,346 missing values generated)

{com}. gen selfest = (est1+ est2 +est3 +est4+ est5)/5  
{txt}(1,988 missing values generated)

{com}. gen SDblack =  (SDbb1+ SDbb2+ SDbb3)/3 
{txt}(2,551 missing values generated)

{com}. gen SDMus =  (SDmu1 +SDmu2 +SDmu3)/3 
{txt}(2,401 missing values generated)

{com}. gen SDEEur =  (SDee1 +SDee2 +SDee3)/3
{txt}(2,563 missing values generated)

{com}. gen GHblack = (GHbb1 +GHbb2 +GHbb3 +GHbb4 +GHbb5 +GHbb6 +GHbb7 +GHbb8)/8
{txt}(2,320 missing values generated)

{com}. gen GHMus = (GHmu1 +GHmu2+ GHmu3 +GHmu4 +GHmu5 +GHmu6 +GHmu7 +GHmu8)/8
{txt}(2,439 missing values generated)

{com}. gen GHEEur = (GHee1 +GHee2 +GHee3+ GHee4 +GHee5 +GHee6+ GHee7+ GHee8)/8
{txt}(2,599 missing values generated)

{com}. gen GHwhite = (GHwb1 +GHwb2+ GHwb3 +GHwb4+ GHwb5 +GHwb6 +GHwb7+ GHwb8)/8
{txt}(2,078 missing values generated)

{com}. 
. * weighting
. mi svyset [pweight=W8]
{res}
      {txt}pweight:{col 16}{res}W8
          {txt}VCE:{col 16}{res}linearized
  {txt}Single unit:{col 16}{res}missing
     {txt}Strata 1:{col 16}<one>
         SU 1:{col 16}<observations>
        FPC 1:{col 16}<zero>
{p2colreset}{...}
{res}{txt}
{com}. 
. * create variable indicating survey wave
. gen wave=0
{txt}
{com}. label define wave 0 "survey wave 1 (2011)" 1 "survey wave 4 (2016)"
{txt}
{com}. label value wave wave
{txt}
{com}. label var wave "survey wave"
{txt}
{com}. 
. save "W1 imputed.dta", replace
{txt}file W1 imputed.dta saved

{com}. 
. 
. *********************************************************************
. * TABLE A.3A IN THE APPENDIX:
. *       Estimated Mean and Standard Error of Imputed Variables, 2011 
. *********************************************************************
. 
. * descriptives: estimated mean and s.e.
. mi estimate: svy: mean authvalues
{res}
{txt}Multiple-imputation estimates{col 35}Imputations{col 51}= {res}        10
{txt}Survey: Mean estimation{col 35}Number of obs{col 51}= {res}       811

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 35}Population size{col 51}={res} 817.642607
{txt}{col 1}Number of PSUs{col 19}= {res}      811
{txt}{col 35}Average RVI{col 51}= {res}    0.0100
{txt}{col 35}Largest FMI{col 51}= {res}    0.0100
{txt}{col 35}Complete DF{col 51}= {res}       810
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 35}DF:     min{col 51}= {res}    792.99
{txt}{col 35}        avg{col 51}= {res}    792.99
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 35}        max{col 51}= {res}    792.99

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 2}authvalues {c |}{col 14}{res}{space 2} 2.186112{col 26}{space 2} .0231776{col 37}{space 5} 2.140615{col 51}{space 3} 2.231609
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}
{res}{txt}
{com}. mi estimate: svy: mean selfest  
{res}
{txt}Multiple-imputation estimates{col 35}Imputations{col 51}= {res}        10
{txt}Survey: Mean estimation{col 35}Number of obs{col 51}= {res}       760

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 35}Population size{col 51}={res} 760.955661
{txt}{col 1}Number of PSUs{col 19}= {res}      760
{txt}{col 35}Average RVI{col 51}= {res}    0.0214
{txt}{col 35}Largest FMI{col 51}= {res}    0.0211
{txt}{col 35}Complete DF{col 51}= {res}       759
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 35}DF:     min{col 51}= {res}    715.18
{txt}{col 35}        avg{col 51}= {res}    715.18
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 35}        max{col 51}= {res}    715.18

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 5}selfest {c |}{col 14}{res}{space 2} .2982862{col 26}{space 2} .0107758{col 37}{space 5} .2771301{col 51}{space 3} .3194422
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}
{res}{txt}
{com}. mi estimate: svy: mean GHblack
{res}
{txt}Multiple-imputation estimates{col 35}Imputations{col 51}= {res}        10
{txt}Survey: Mean estimation{col 35}Number of obs{col 51}= {res}       732

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 35}Population size{col 51}={res} 731.915439
{txt}{col 1}Number of PSUs{col 19}= {res}      732
{txt}{col 35}Average RVI{col 51}= {res}    0.1382
{txt}{col 35}Largest FMI{col 51}= {res}    0.1246
{txt}{col 35}Complete DF{col 51}= {res}       731
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 35}DF:     min{col 51}= {res}    312.59
{txt}{col 35}        avg{col 51}= {res}    312.59
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 35}        max{col 51}= {res}    312.59

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 5}GHblack {c |}{col 14}{res}{space 2} 2.139731{col 26}{space 2} .0255878{col 37}{space 5} 2.089385{col 51}{space 3} 2.190077
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}
{res}{txt}
{com}. mi estimate: svy: mean GHMus
{res}
{txt}Multiple-imputation estimates{col 35}Imputations{col 51}= {res}        10
{txt}Survey: Mean estimation{col 35}Number of obs{col 51}= {res}       723

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 35}Population size{col 51}={res} 719.942589
{txt}{col 1}Number of PSUs{col 19}= {res}      723
{txt}{col 35}Average RVI{col 51}= {res}    0.0537
{txt}{col 35}Largest FMI{col 51}= {res}    0.0516
{txt}{col 35}Complete DF{col 51}= {res}       722
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 35}DF:     min{col 51}= {res}    570.81
{txt}{col 35}        avg{col 51}= {res}    570.81
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 35}        max{col 51}= {res}    570.81

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 7}GHMus {c |}{col 14}{res}{space 2} 2.261997{col 26}{space 2} .0278112{col 37}{space 5} 2.207372{col 51}{space 3} 2.316621
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}
{res}{txt}
{com}. mi estimate: svy: mean GHEEur
{res}
{txt}Multiple-imputation estimates{col 35}Imputations{col 51}= {res}        10
{txt}Survey: Mean estimation{col 35}Number of obs{col 51}= {res}       710

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 35}Population size{col 51}={res} 711.703502
{txt}{col 1}Number of PSUs{col 19}= {res}      710
{txt}{col 35}Average RVI{col 51}= {res}    0.0691
{txt}{col 35}Largest FMI{col 51}= {res}    0.0657
{txt}{col 35}Complete DF{col 51}= {res}       709
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 35}DF:     min{col 51}= {res}    506.06
{txt}{col 35}        avg{col 51}= {res}    506.06
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 35}        max{col 51}= {res}    506.06

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 6}GHEEur {c |}{col 14}{res}{space 2} 2.167698{col 26}{space 2} .0260044{col 37}{space 5} 2.116608{col 51}{space 3} 2.218788
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}
{res}{txt}
{com}. mi estimate: svy: mean GHwhite
{res}
{txt}Multiple-imputation estimates{col 35}Imputations{col 51}= {res}        10
{txt}Survey: Mean estimation{col 35}Number of obs{col 51}= {res}       770

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 35}Population size{col 51}={res} 772.805253
{txt}{col 1}Number of PSUs{col 19}= {res}      770
{txt}{col 35}Average RVI{col 51}= {res}    0.0739
{txt}{col 35}Largest FMI{col 51}= {res}    0.0700
{txt}{col 35}Complete DF{col 51}= {res}       769
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 35}DF:     min{col 51}= {res}    519.19
{txt}{col 35}        avg{col 51}= {res}    519.19
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 35}        max{col 51}= {res}    519.19

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 5}GHwhite {c |}{col 14}{res}{space 2} 2.659834{col 26}{space 2} .0637284{col 37}{space 5} 2.534637{col 51}{space 3} 2.785032
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}
{res}{txt}
{com}. 
. * descriptives: minimum and maximum
. sum authvalues selfest GHblack GHMus GHEEur GHwhite 

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 2}authvalues {c |}{res}      8,093    2.152623    .6410499   .9124531   4.224614
{txt}{space 5}selfest {c |}{res}      7,451    .2838001    .2687766  -.3121713   1.042753
{txt}{space 5}GHblack {c |}{res}      7,119    2.113725    .6275206   .6240878   4.330703
{txt}{space 7}GHMus {c |}{res}      7,000    2.229131    .7145052   .3172066   4.482132
{txt}{space 6}GHEEur {c |}{res}      6,840    2.139639     .646766  -.3294929   4.342618
{txt}{hline 13}{c +}{hline 57}
{space 5}GHwhite {c |}{res}      7,361    2.722204    1.621853  -1.877937   6.342162
{txt}
{com}. 
. 
. *********************************************************************
. * TABLE A.5 IN THE APPENDIX:
. *       Predictors of Threat under Coupled (C) and Decoupled (D) Conditions, 2011
. *********************************************************************
. 
. * coupled
. mi estimate: svy: oprobit threat1 female Age edu_age i.SocialGrade i.work_status UKborn Bidentity_2 retroecon retrofin authvalues selfest if treatment==1 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Ordered probit regression{col 49}Number of obs{col 67}= {res}       252

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 249.781502
{txt}{col 1}Number of PSUs{col 19}= {res}      252
{txt}{col 49}Average RVI{col 67}= {res}    0.0026
{txt}{col 49}Largest FMI{col 67}= {res}    0.0140
{txt}{col 49}Complete DF{col 67}= {res}       251
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    244.32
{txt}{col 49}        avg{col 67}= {res}    248.43
{txt}{col 49}        max{col 67}= {res}    248.94
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  17{txt},{res}  249.0{txt}){col 67}= {res}      3.98
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           threat1{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}female {c |}{col 20}{res}{space 2}-.2493032{col 32}{space 2} .1508115{col 43}{space 1}   -1.65{col 52}{space 3}0.100{col 60}{space 4}-.5463351{col 73}{space 3} .0477287
{txt}{space 15}Age {c |}{col 20}{res}{space 2} .0030003{col 32}{space 2} .0074361{col 43}{space 1}    0.40{col 52}{space 3}0.687{col 60}{space 4}-.0116455{col 73}{space 3} .0176461
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0001368{col 32}{space 2} .0471579{col 43}{space 1}   -0.00{col 52}{space 3}0.998{col 60}{space 4}-.0930167{col 73}{space 3} .0927431
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2} .0988783{col 32}{space 2} .1769442{col 43}{space 1}    0.56{col 52}{space 3}0.577{col 60}{space 4}-.2496242{col 73}{space 3} .4473809
{txt}{space 15}C2  {c |}{col 20}{res}{space 2} .1255341{col 32}{space 2} .2502827{col 43}{space 1}    0.50{col 52}{space 3}0.616{col 60}{space 4}-.3674124{col 73}{space 3} .6184805
{txt}{space 15}DE  {c |}{col 20}{res}{space 2} .3216524{col 32}{space 2} .2503373{col 43}{space 1}    1.28{col 52}{space 3}0.200{col 60}{space 4}-.1713977{col 73}{space 3} .8147025
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2} .0488435{col 32}{space 2} .2749612{col 43}{space 1}    0.18{col 52}{space 3}0.859{col 60}{space 4}-.4927037{col 73}{space 3} .5903908
{txt}full time student  {c |}{col 20}{res}{space 2} .2443845{col 32}{space 2} .3272893{col 43}{space 1}    0.75{col 52}{space 3}0.456{col 60}{space 4}-.4002322{col 73}{space 3} .8890013
{txt}{space 10}retired  {c |}{col 20}{res}{space 2}-.1737966{col 32}{space 2} .2483745{col 43}{space 1}   -0.70{col 52}{space 3}0.485{col 60}{space 4}-.6629802{col 73}{space 3} .3153871
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2}-.0831651{col 32}{space 2} .4155303{col 43}{space 1}   -0.20{col 52}{space 3}0.842{col 60}{space 4}-.9015683{col 73}{space 3} .7352381
{txt}{space 6}not working  {c |}{col 20}{res}{space 2} .4007542{col 32}{space 2} .2865042{col 43}{space 1}    1.40{col 52}{space 3}0.163{col 60}{space 4}-.1635306{col 73}{space 3}  .965039
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2} .6439352{col 32}{space 2} .4033826{col 43}{space 1}    1.60{col 52}{space 3}0.112{col 60}{space 4}-.1505456{col 73}{space 3} 1.438416
{txt}{space 7}Bidentity_2 {c |}{col 20}{res}{space 2} .3670415{col 32}{space 2}  .128479{col 43}{space 1}    2.86{col 52}{space 3}0.005{col 60}{space 4} .1139965{col 73}{space 3} .6200864
{txt}{space 9}retroecon {c |}{col 20}{res}{space 2}-.1121552{col 32}{space 2}  .079438{col 43}{space 1}   -1.41{col 52}{space 3}0.159{col 60}{space 4}-.2686116{col 73}{space 3} .0443012
{txt}{space 10}retrofin {c |}{col 20}{res}{space 2}-.0697424{col 32}{space 2} .0957482{col 43}{space 1}   -0.73{col 52}{space 3}0.467{col 60}{space 4}-.2583223{col 73}{space 3} .1188374
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .6409423{col 32}{space 2} .1471932{col 43}{space 1}    4.35{col 52}{space 3}0.000{col 60}{space 4} .3510371{col 73}{space 3} .9308475
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .3388795{col 32}{space 2} .3084311{col 43}{space 1}    1.10{col 52}{space 3}0.273{col 60}{space 4}-.2686437{col 73}{space 3} .9464028
{txt}{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
             /cut1 {c |}{col 20}{res}{space 2} 2.417744{col 32}{space 2} 1.192577{col 43}{space 1}    2.03{col 52}{space 3}0.044{col 60}{space 4}  .068896{col 73}{space 3} 4.766592
{txt}             /cut2 {c |}{col 20}{res}{space 2} 3.559142{col 32}{space 2} 1.201602{col 43}{space 1}    2.96{col 52}{space 3}0.003{col 60}{space 4} 1.192519{col 73}{space 3} 5.925765
{txt}             /cut3 {c |}{col 20}{res}{space 2}  4.42218{col 32}{space 2} 1.216892{col 43}{space 1}    3.63{col 52}{space 3}0.000{col 60}{space 4} 2.025442{col 73}{space 3} 6.818918
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. * decoupled
. mi estimate: svy: oprobit threat1 female Age edu_age i.SocialGrade i.work_status UKborn Bidentity_2 retroecon retrofin authvalues selfest if treatment==0 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Ordered probit regression{col 49}Number of obs{col 67}= {res}       437

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 437.851427
{txt}{col 1}Number of PSUs{col 19}= {res}      437
{txt}{col 49}Average RVI{col 67}= {res}    0.0047
{txt}{col 49}Largest FMI{col 67}= {res}    0.0464
{txt}{col 49}Complete DF{col 67}= {res}       436
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    377.83
{txt}{col 49}        avg{col 67}= {res}    429.40
{txt}{col 49}        max{col 67}= {res}    433.93
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  17{txt},{res}  434.0{txt}){col 67}= {res}      4.43
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           threat1{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}female {c |}{col 20}{res}{space 2} .2594759{col 32}{space 2} .1203219{col 43}{space 1}    2.16{col 52}{space 3}0.032{col 60}{space 4} .0229873{col 73}{space 3} .4959645
{txt}{space 15}Age {c |}{col 20}{res}{space 2} -.006196{col 32}{space 2}  .005399{col 43}{space 1}   -1.15{col 52}{space 3}0.252{col 60}{space 4}-.0168076{col 73}{space 3} .0044156
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0740352{col 32}{space 2} .0362467{col 43}{space 1}   -2.04{col 52}{space 3}0.042{col 60}{space 4}-.1452763{col 73}{space 3} -.002794
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2}-.0504392{col 32}{space 2} .1279006{col 43}{space 1}   -0.39{col 52}{space 3}0.694{col 60}{space 4}-.3018218{col 73}{space 3} .2009433
{txt}{space 15}C2  {c |}{col 20}{res}{space 2} .1053273{col 32}{space 2} .2012008{col 43}{space 1}    0.52{col 52}{space 3}0.601{col 60}{space 4} -.290123{col 73}{space 3} .5007776
{txt}{space 15}DE  {c |}{col 20}{res}{space 2}  .279893{col 32}{space 2} .1798618{col 43}{space 1}    1.56{col 52}{space 3}0.120{col 60}{space 4}-.0736163{col 73}{space 3} .6334023
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2}-.2885366{col 32}{space 2} .1887003{col 43}{space 1}   -1.53{col 52}{space 3}0.127{col 60}{space 4}-.6594183{col 73}{space 3}  .082345
{txt}full time student  {c |}{col 20}{res}{space 2}-.3734913{col 32}{space 2} .3892435{col 43}{space 1}   -0.96{col 52}{space 3}0.338{col 60}{space 4}-1.138528{col 73}{space 3} .3915457
{txt}{space 10}retired  {c |}{col 20}{res}{space 2}-.0875894{col 32}{space 2} .1797963{col 43}{space 1}   -0.49{col 52}{space 3}0.626{col 60}{space 4}-.4409714{col 73}{space 3} .2657927
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2}-.9080666{col 32}{space 2} .3779725{col 43}{space 1}   -2.40{col 52}{space 3}0.017{col 60}{space 4}-1.650957{col 73}{space 3}-.1651764
{txt}{space 6}not working  {c |}{col 20}{res}{space 2}-.1577767{col 32}{space 2} .1858395{col 43}{space 1}   -0.85{col 52}{space 3}0.396{col 60}{space 4}-.5230392{col 73}{space 3} .2074858
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2} -.323071{col 32}{space 2} .2474993{col 43}{space 1}   -1.31{col 52}{space 3}0.192{col 60}{space 4}-.8095185{col 73}{space 3} .1633764
{txt}{space 7}Bidentity_2 {c |}{col 20}{res}{space 2} .1123123{col 32}{space 2} .1038456{col 43}{space 1}    1.08{col 52}{space 3}0.280{col 60}{space 4}-.0917913{col 73}{space 3}  .316416
{txt}{space 9}retroecon {c |}{col 20}{res}{space 2}-.1074508{col 32}{space 2} .0748547{col 43}{space 1}   -1.44{col 52}{space 3}0.152{col 60}{space 4} -.254574{col 73}{space 3} .0396723
{txt}{space 10}retrofin {c |}{col 20}{res}{space 2}-.1732379{col 32}{space 2} .0791074{col 43}{space 1}   -2.19{col 52}{space 3}0.029{col 60}{space 4}-.3287196{col 73}{space 3}-.0177562
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2}  .150117{col 32}{space 2} .0976995{col 43}{space 1}    1.54{col 52}{space 3}0.125{col 60}{space 4}-.0419295{col 73}{space 3} .3421634
{txt}{space 11}selfest {c |}{col 20}{res}{space 2}  .558732{col 32}{space 2} .2268887{col 43}{space 1}    2.46{col 52}{space 3}0.014{col 60}{space 4} .1126092{col 73}{space 3} 1.004855
{txt}{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
             /cut1 {c |}{col 20}{res}{space 2}-2.944305{col 32}{space 2} .9986791{col 43}{space 1}   -2.95{col 52}{space 3}0.003{col 60}{space 4}-4.907173{col 73}{space 3}-.9814361
{txt}             /cut2 {c |}{col 20}{res}{space 2}-1.552282{col 32}{space 2} .9997504{col 43}{space 1}   -1.55{col 52}{space 3}0.121{col 60}{space 4}-3.517257{col 73}{space 3}  .412693
{txt}             /cut3 {c |}{col 20}{res}{space 2}-.3980093{col 32}{space 2}  1.00135{col 43}{space 1}   -0.40{col 52}{space 3}0.691{col 60}{space 4}-2.366129{col 73}{space 3} 1.570111
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. * coupled
. mi estimate: svy: oprobit threat2 female Age edu_age i.SocialGrade i.work_status UKborn Bidentity_2 retroecon retrofin authvalues selfest if treatment==1 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Ordered probit regression{col 49}Number of obs{col 67}= {res}       248

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 247.964119
{txt}{col 1}Number of PSUs{col 19}= {res}      248
{txt}{col 49}Average RVI{col 67}= {res}    0.0031
{txt}{col 49}Largest FMI{col 67}= {res}    0.0227
{txt}{col 49}Complete DF{col 67}= {res}       247
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    236.40
{txt}{col 49}        avg{col 67}= {res}    244.10
{txt}{col 49}        max{col 67}= {res}    244.90
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  17{txt},{res}  245.0{txt}){col 67}= {res}      5.09
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           threat2{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}female {c |}{col 20}{res}{space 2}-.0304843{col 32}{space 2} .1554674{col 43}{space 1}   -0.20{col 52}{space 3}0.845{col 60}{space 4}-.3367101{col 73}{space 3} .2757414
{txt}{space 15}Age {c |}{col 20}{res}{space 2} .0032975{col 32}{space 2} .0077377{col 43}{space 1}    0.43{col 52}{space 3}0.670{col 60}{space 4}-.0119437{col 73}{space 3} .0185387
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0690852{col 32}{space 2} .0484052{col 43}{space 1}   -1.43{col 52}{space 3}0.155{col 60}{space 4}-.1644297{col 73}{space 3} .0262592
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2} .0436305{col 32}{space 2} .1803951{col 43}{space 1}    0.24{col 52}{space 3}0.809{col 60}{space 4}-.3116977{col 73}{space 3} .3989587
{txt}{space 15}C2  {c |}{col 20}{res}{space 2} .1337382{col 32}{space 2} .3422131{col 43}{space 1}    0.39{col 52}{space 3}0.696{col 60}{space 4}-.5403205{col 73}{space 3} .8077969
{txt}{space 15}DE  {c |}{col 20}{res}{space 2} .2981205{col 32}{space 2} .1989255{col 43}{space 1}    1.50{col 52}{space 3}0.135{col 60}{space 4}-.0937031{col 73}{space 3} .6899441
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2} .2281066{col 32}{space 2} .2709804{col 43}{space 1}    0.84{col 52}{space 3}0.401{col 60}{space 4}-.3056431{col 73}{space 3} .7618564
{txt}full time student  {c |}{col 20}{res}{space 2} .1114447{col 32}{space 2} .4704047{col 43}{space 1}    0.24{col 52}{space 3}0.813{col 60}{space 4}-.8151155{col 73}{space 3} 1.038005
{txt}{space 10}retired  {c |}{col 20}{res}{space 2}-.5317053{col 32}{space 2} .2858473{col 43}{space 1}   -1.86{col 52}{space 3}0.064{col 60}{space 4}-1.094739{col 73}{space 3} .0313282
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2} -.115391{col 32}{space 2} .3298942{col 43}{space 1}   -0.35{col 52}{space 3}0.727{col 60}{space 4}-.7651888{col 73}{space 3} .5344068
{txt}{space 6}not working  {c |}{col 20}{res}{space 2} .1699043{col 32}{space 2} .2443277{col 43}{space 1}    0.70{col 52}{space 3}0.487{col 60}{space 4}-.3113555{col 73}{space 3} .6511641
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2} .5709444{col 32}{space 2} .6823545{col 43}{space 1}    0.84{col 52}{space 3}0.404{col 60}{space 4}-.7730889{col 73}{space 3} 1.914978
{txt}{space 7}Bidentity_2 {c |}{col 20}{res}{space 2} .3698767{col 32}{space 2} .1286561{col 43}{space 1}    2.87{col 52}{space 3}0.004{col 60}{space 4} .1164628{col 73}{space 3} .6232906
{txt}{space 9}retroecon {c |}{col 20}{res}{space 2}-.0602305{col 32}{space 2} .0839278{col 43}{space 1}   -0.72{col 52}{space 3}0.474{col 60}{space 4}-.2255429{col 73}{space 3} .1050818
{txt}{space 10}retrofin {c |}{col 20}{res}{space 2}-.3278146{col 32}{space 2} .0892316{col 43}{space 1}   -3.67{col 52}{space 3}0.000{col 60}{space 4}-.5035739{col 73}{space 3}-.1520553
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .6069901{col 32}{space 2} .1360092{col 43}{space 1}    4.46{col 52}{space 3}0.000{col 60}{space 4} .3390779{col 73}{space 3} .8749024
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .5602634{col 32}{space 2} .3159225{col 43}{space 1}    1.77{col 52}{space 3}0.077{col 60}{space 4}-.0621196{col 73}{space 3} 1.182646
{txt}{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
             /cut1 {c |}{col 20}{res}{space 2} .4683885{col 32}{space 2} 1.424983{col 43}{space 1}    0.33{col 52}{space 3}0.743{col 60}{space 4}-2.338415{col 73}{space 3} 3.275192
{txt}             /cut2 {c |}{col 20}{res}{space 2} 1.469818{col 32}{space 2}  1.43366{col 43}{space 1}    1.03{col 52}{space 3}0.306{col 60}{space 4}-1.354077{col 73}{space 3} 4.293712
{txt}             /cut3 {c |}{col 20}{res}{space 2} 2.504426{col 32}{space 2} 1.454395{col 43}{space 1}    1.72{col 52}{space 3}0.086{col 60}{space 4}-.3603108{col 73}{space 3} 5.369163
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. * decoupled
. mi estimate: svy: oprobit threat2 female Age edu_age i.SocialGrade i.work_status UKborn Bidentity_2 retroecon retrofin authvalues selfest if treatment==0 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Ordered probit regression{col 49}Number of obs{col 67}= {res}       437

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 437.851427
{txt}{col 1}Number of PSUs{col 19}= {res}      437
{txt}{col 49}Average RVI{col 67}= {res}    0.0115
{txt}{col 49}Largest FMI{col 67}= {res}    0.1044
{txt}{col 49}Complete DF{col 67}= {res}       436
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    268.88
{txt}{col 49}        avg{col 67}= {res}    417.39
{txt}{col 49}        max{col 67}= {res}    433.89
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  17{txt},{res}  433.7{txt}){col 67}= {res}      7.93
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           threat2{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}female {c |}{col 20}{res}{space 2} .2267316{col 32}{space 2} .1218734{col 43}{space 1}    1.86{col 52}{space 3}0.064{col 60}{space 4}-.0128052{col 73}{space 3} .4662683
{txt}{space 15}Age {c |}{col 20}{res}{space 2}-.0048316{col 32}{space 2} .0060399{col 43}{space 1}   -0.80{col 52}{space 3}0.424{col 60}{space 4}-.0167031{col 73}{space 3} .0070398
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2} -.068618{col 32}{space 2} .0387024{col 43}{space 1}   -1.77{col 52}{space 3}0.077{col 60}{space 4}-.1446864{col 73}{space 3} .0074503
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2} .0028039{col 32}{space 2} .1441023{col 43}{space 1}    0.02{col 52}{space 3}0.984{col 60}{space 4}-.2804224{col 73}{space 3} .2860303
{txt}{space 15}C2  {c |}{col 20}{res}{space 2} .0709193{col 32}{space 2} .1788892{col 43}{space 1}    0.40{col 52}{space 3}0.692{col 60}{space 4}-.2806786{col 73}{space 3} .4225172
{txt}{space 15}DE  {c |}{col 20}{res}{space 2} .2691702{col 32}{space 2} .1892854{col 43}{space 1}    1.42{col 52}{space 3}0.156{col 60}{space 4}-.1028601{col 73}{space 3} .6412006
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2}-.3032186{col 32}{space 2}  .181987{col 43}{space 1}   -1.67{col 52}{space 3}0.096{col 60}{space 4}-.6609061{col 73}{space 3} .0544689
{txt}full time student  {c |}{col 20}{res}{space 2} .1654879{col 32}{space 2} .3327604{col 43}{space 1}    0.50{col 52}{space 3}0.619{col 60}{space 4}-.4885353{col 73}{space 3} .8195112
{txt}{space 10}retired  {c |}{col 20}{res}{space 2}-.4843295{col 32}{space 2} .2062411{col 43}{space 1}   -2.35{col 52}{space 3}0.019{col 60}{space 4}-.8896874{col 73}{space 3}-.0789717
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2}-.3661979{col 32}{space 2} .3512802{col 43}{space 1}   -1.04{col 52}{space 3}0.298{col 60}{space 4}-1.056631{col 73}{space 3} .3242352
{txt}{space 6}not working  {c |}{col 20}{res}{space 2} .0109563{col 32}{space 2} .2182118{col 43}{space 1}    0.05{col 52}{space 3}0.960{col 60}{space 4}-.4179299{col 73}{space 3} .4398425
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2} .3054654{col 32}{space 2} .3159088{col 43}{space 1}    0.97{col 52}{space 3}0.334{col 60}{space 4}-.3154371{col 73}{space 3} .9263679
{txt}{space 7}Bidentity_2 {c |}{col 20}{res}{space 2} .0122532{col 32}{space 2} .1135159{col 43}{space 1}    0.11{col 52}{space 3}0.914{col 60}{space 4}-.2108577{col 73}{space 3}  .235364
{txt}{space 9}retroecon {c |}{col 20}{res}{space 2}-.2711427{col 32}{space 2}  .080388{col 43}{space 1}   -3.37{col 52}{space 3}0.001{col 60}{space 4}-.4291413{col 73}{space 3} -.113144
{txt}{space 10}retrofin {c |}{col 20}{res}{space 2}-.6002136{col 32}{space 2} .0805848{col 43}{space 1}   -7.45{col 52}{space 3}0.000{col 60}{space 4}-.7585988{col 73}{space 3}-.4418283
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2}  -.07058{col 32}{space 2} .1073141{col 43}{space 1}   -0.66{col 52}{space 3}0.511{col 60}{space 4}-.2817824{col 73}{space 3} .1406224
{txt}{space 11}selfest {c |}{col 20}{res}{space 2}  .467586{col 32}{space 2}  .263278{col 43}{space 1}    1.78{col 52}{space 3}0.077{col 60}{space 4}-.0507626{col 73}{space 3} .9859347
{txt}{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
             /cut1 {c |}{col 20}{res}{space 2}-5.552724{col 32}{space 2} 1.120567{col 43}{space 1}   -4.96{col 52}{space 3}0.000{col 60}{space 4}-7.755195{col 73}{space 3}-3.350254
{txt}             /cut2 {c |}{col 20}{res}{space 2}-4.015495{col 32}{space 2} 1.125355{col 43}{space 1}   -3.57{col 52}{space 3}0.000{col 60}{space 4}-6.227372{col 73}{space 3}-1.803618
{txt}             /cut3 {c |}{col 20}{res}{space 2} -2.16923{col 32}{space 2} 1.116767{col 43}{space 1}   -1.94{col 52}{space 3}0.053{col 60}{space 4}-4.364228{col 73}{space 3} .0257679
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. * coupled
. mi estimate: svy: oprobit threat3 female Age edu_age i.SocialGrade i.work_status UKborn Bidentity_2 retroecon retrofin authvalues selfest if treatment==1 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Ordered probit regression{col 49}Number of obs{col 67}= {res}       254

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 254.593346
{txt}{col 1}Number of PSUs{col 19}= {res}      254
{txt}{col 49}Average RVI{col 67}= {res}    0.0036
{txt}{col 49}Largest FMI{col 67}= {res}    0.0367
{txt}{col 49}Complete DF{col 67}= {res}       253
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    233.78
{txt}{col 49}        avg{col 67}= {res}    249.66
{txt}{col 49}        max{col 67}= {res}    250.99
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  17{txt},{res}  251.0{txt}){col 67}= {res}      3.71
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           threat3{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}female {c |}{col 20}{res}{space 2}-.1343185{col 32}{space 2} .1454915{col 43}{space 1}   -0.92{col 52}{space 3}0.357{col 60}{space 4}-.4208608{col 73}{space 3} .1522237
{txt}{space 15}Age {c |}{col 20}{res}{space 2} .0040133{col 32}{space 2} .0069711{col 43}{space 1}    0.58{col 52}{space 3}0.565{col 60}{space 4}-.0097163{col 73}{space 3} .0177429
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.1138267{col 32}{space 2} .0481603{col 43}{space 1}   -2.36{col 52}{space 3}0.019{col 60}{space 4}-.2086768{col 73}{space 3}-.0189766
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2} -.088148{col 32}{space 2} .1875189{col 43}{space 1}   -0.47{col 52}{space 3}0.639{col 60}{space 4}-.4574629{col 73}{space 3}  .281167
{txt}{space 15}C2  {c |}{col 20}{res}{space 2}-.1315639{col 32}{space 2} .2531898{col 43}{space 1}   -0.52{col 52}{space 3}0.604{col 60}{space 4}-.6302191{col 73}{space 3} .3670913
{txt}{space 15}DE  {c |}{col 20}{res}{space 2} .2179146{col 32}{space 2} .2115232{col 43}{space 1}    1.03{col 52}{space 3}0.304{col 60}{space 4}-.1986752{col 73}{space 3} .6345045
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2}  .108361{col 32}{space 2} .2743464{col 43}{space 1}    0.39{col 52}{space 3}0.693{col 60}{space 4} -.431954{col 73}{space 3}  .648676
{txt}full time student  {c |}{col 20}{res}{space 2} .4515777{col 32}{space 2} .3336101{col 43}{space 1}    1.35{col 52}{space 3}0.177{col 60}{space 4} -.205458{col 73}{space 3} 1.108613
{txt}{space 10}retired  {c |}{col 20}{res}{space 2}-.2031646{col 32}{space 2} .2341313{col 43}{space 1}   -0.87{col 52}{space 3}0.386{col 60}{space 4} -.664277{col 73}{space 3} .2579478
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2}-.1783611{col 32}{space 2} .3896047{col 43}{space 1}   -0.46{col 52}{space 3}0.647{col 60}{space 4} -.945675{col 73}{space 3} .5889529
{txt}{space 6}not working  {c |}{col 20}{res}{space 2} .0907616{col 32}{space 2} .2591031{col 43}{space 1}    0.35{col 52}{space 3}0.726{col 60}{space 4} -.419538{col 73}{space 3} .6010613
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2} .7882634{col 32}{space 2} .4500313{col 43}{space 1}    1.75{col 52}{space 3}0.081{col 60}{space 4}-.0980605{col 73}{space 3} 1.674587
{txt}{space 7}Bidentity_2 {c |}{col 20}{res}{space 2} .3191252{col 32}{space 2} .1228911{col 43}{space 1}    2.60{col 52}{space 3}0.010{col 60}{space 4} .0770953{col 73}{space 3} .5611552
{txt}{space 9}retroecon {c |}{col 20}{res}{space 2}-.0230256{col 32}{space 2} .0701153{col 43}{space 1}   -0.33{col 52}{space 3}0.743{col 60}{space 4}-.1611154{col 73}{space 3} .1150641
{txt}{space 10}retrofin {c |}{col 20}{res}{space 2}-.2052113{col 32}{space 2} .0863282{col 43}{space 1}   -2.38{col 52}{space 3}0.018{col 60}{space 4}-.3752314{col 73}{space 3}-.0351911
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .5232838{col 32}{space 2} .1373083{col 43}{space 1}    3.81{col 52}{space 3}0.000{col 60}{space 4} .2528442{col 73}{space 3} .7937233
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .0579204{col 32}{space 2} .2949287{col 43}{space 1}    0.20{col 52}{space 3}0.844{col 60}{space 4}-.5231374{col 73}{space 3} .6389781
{txt}{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
             /cut1 {c |}{col 20}{res}{space 2}  -.45235{col 32}{space 2} 1.316904{col 43}{space 1}   -0.34{col 52}{space 3}0.732{col 60}{space 4}-3.045961{col 73}{space 3} 2.141261
{txt}             /cut2 {c |}{col 20}{res}{space 2} .4958136{col 32}{space 2} 1.323119{col 43}{space 1}    0.37{col 52}{space 3}0.708{col 60}{space 4}-2.110038{col 73}{space 3} 3.101666
{txt}             /cut3 {c |}{col 20}{res}{space 2} 1.588366{col 32}{space 2} 1.331358{col 43}{space 1}    1.19{col 52}{space 3}0.234{col 60}{space 4}-1.033713{col 73}{space 3} 4.210446
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. * decoupled
. mi estimate: svy: oprobit threat3 female Age edu_age i.SocialGrade i.work_status UKborn Bidentity_2 retroecon retrofin authvalues selfest if treatment==0    
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Ordered probit regression{col 49}Number of obs{col 67}= {res}       439

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 439.717339
{txt}{col 1}Number of PSUs{col 19}= {res}      439
{txt}{col 49}Average RVI{col 67}= {res}    0.0066
{txt}{col 49}Largest FMI{col 67}= {res}    0.0777
{txt}{col 49}Complete DF{col 67}= {res}       438
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    319.79
{txt}{col 49}        avg{col 67}= {res}    428.12
{txt}{col 49}        max{col 67}= {res}    435.89
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  17{txt},{res}  435.9{txt}){col 67}= {res}      5.72
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           threat3{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}female {c |}{col 20}{res}{space 2} .4138495{col 32}{space 2} .1179247{col 43}{space 1}    3.51{col 52}{space 3}0.000{col 60}{space 4} .1820761{col 73}{space 3} .6456229
{txt}{space 15}Age {c |}{col 20}{res}{space 2} .0022762{col 32}{space 2} .0056865{col 43}{space 1}    0.40{col 52}{space 3}0.689{col 60}{space 4}-.0089004{col 73}{space 3} .0134528
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0933477{col 32}{space 2} .0365168{col 43}{space 1}   -2.56{col 52}{space 3}0.011{col 60}{space 4}-.1651189{col 73}{space 3}-.0215765
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2} -.006253{col 32}{space 2} .1343537{col 43}{space 1}   -0.05{col 52}{space 3}0.963{col 60}{space 4}-.2703149{col 73}{space 3} .2578089
{txt}{space 15}C2  {c |}{col 20}{res}{space 2} .1470056{col 32}{space 2}  .172772{col 43}{space 1}    0.85{col 52}{space 3}0.395{col 60}{space 4}-.1925652{col 73}{space 3} .4865763
{txt}{space 15}DE  {c |}{col 20}{res}{space 2} .1034851{col 32}{space 2} .1834288{col 43}{space 1}    0.56{col 52}{space 3}0.573{col 60}{space 4}-.2570307{col 73}{space 3} .4640008
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2}-.4280903{col 32}{space 2} .1891631{col 43}{space 1}   -2.26{col 52}{space 3}0.024{col 60}{space 4}-.7998763{col 73}{space 3}-.0563043
{txt}full time student  {c |}{col 20}{res}{space 2}-.2701874{col 32}{space 2} .3761827{col 43}{space 1}   -0.72{col 52}{space 3}0.473{col 60}{space 4}-1.009545{col 73}{space 3} .4691704
{txt}{space 10}retired  {c |}{col 20}{res}{space 2}-.1704028{col 32}{space 2} .1889356{col 43}{space 1}   -0.90{col 52}{space 3}0.368{col 60}{space 4}-.5417425{col 73}{space 3} .2009368
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2}-.5163567{col 32}{space 2} .3977282{col 43}{space 1}   -1.30{col 52}{space 3}0.195{col 60}{space 4}-1.298065{col 73}{space 3} .2653513
{txt}{space 6}not working  {c |}{col 20}{res}{space 2}-.3021225{col 32}{space 2} .2091497{col 43}{space 1}   -1.44{col 52}{space 3}0.149{col 60}{space 4}-.7132006{col 73}{space 3} .1089556
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2}-.8532713{col 32}{space 2} .4116668{col 43}{space 1}   -2.07{col 52}{space 3}0.039{col 60}{space 4} -1.66237{col 73}{space 3}-.0441726
{txt}{space 7}Bidentity_2 {c |}{col 20}{res}{space 2} .1842471{col 32}{space 2}   .10443{col 43}{space 1}    1.76{col 52}{space 3}0.078{col 60}{space 4}-.0210027{col 73}{space 3} .3894968
{txt}{space 9}retroecon {c |}{col 20}{res}{space 2}-.1848014{col 32}{space 2} .0707812{col 43}{space 1}   -2.61{col 52}{space 3}0.009{col 60}{space 4}-.3239165{col 73}{space 3}-.0456863
{txt}{space 10}retrofin {c |}{col 20}{res}{space 2}-.1371217{col 32}{space 2} .0765247{col 43}{space 1}   -1.79{col 52}{space 3}0.074{col 60}{space 4}-.2875259{col 73}{space 3} .0132826
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .2106476{col 32}{space 2} .0997511{col 43}{space 1}    2.11{col 52}{space 3}0.035{col 60}{space 4} .0145666{col 73}{space 3} .4067286
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .2857528{col 32}{space 2} .2297653{col 43}{space 1}    1.24{col 52}{space 3}0.215{col 60}{space 4}-.1662897{col 73}{space 3} .7377952
{txt}{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
             /cut1 {c |}{col 20}{res}{space 2}-3.647294{col 32}{space 2} 1.053959{col 43}{space 1}   -3.46{col 52}{space 3}0.001{col 60}{space 4}-5.718783{col 73}{space 3}-1.575805
{txt}             /cut2 {c |}{col 20}{res}{space 2}-2.521463{col 32}{space 2} 1.061448{col 43}{space 1}   -2.38{col 52}{space 3}0.018{col 60}{space 4}-4.607671{col 73}{space 3}-.4352547
{txt}             /cut3 {c |}{col 20}{res}{space 2}-1.078519{col 32}{space 2} 1.061062{col 43}{space 1}   -1.02{col 52}{space 3}0.310{col 60}{space 4}-3.163972{col 73}{space 3} 1.006933
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. * coupled
. mi estimate: svy: oprobit threat4 female Age edu_age i.SocialGrade i.work_status UKborn Bidentity_2 retroecon retrofin authvalues selfest if treatment==1 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Ordered probit regression{col 49}Number of obs{col 67}= {res}       252

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 252.114358
{txt}{col 1}Number of PSUs{col 19}= {res}      252
{txt}{col 49}Average RVI{col 67}= {res}    0.0032
{txt}{col 49}Largest FMI{col 67}= {res}    0.0314
{txt}{col 49}Complete DF{col 67}= {res}       251
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    235.33
{txt}{col 49}        avg{col 67}= {res}    247.94
{txt}{col 49}        max{col 67}= {res}    249.00
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  17{txt},{res}  249.0{txt}){col 67}= {res}      3.70
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           threat4{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}female {c |}{col 20}{res}{space 2}-.0419678{col 32}{space 2}  .153524{col 43}{space 1}   -0.27{col 52}{space 3}0.785{col 60}{space 4}-.3443405{col 73}{space 3} .2604049
{txt}{space 15}Age {c |}{col 20}{res}{space 2}-.0014199{col 32}{space 2} .0076379{col 43}{space 1}   -0.19{col 52}{space 3}0.853{col 60}{space 4}-.0164632{col 73}{space 3} .0136233
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2} -.110703{col 32}{space 2} .0519661{col 43}{space 1}   -2.13{col 52}{space 3}0.034{col 60}{space 4}-.2130527{col 73}{space 3}-.0083534
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2} .0195123{col 32}{space 2} .1717203{col 43}{space 1}    0.11{col 52}{space 3}0.910{col 60}{space 4}-.3186999{col 73}{space 3} .3577244
{txt}{space 15}C2  {c |}{col 20}{res}{space 2} .0451875{col 32}{space 2} .2817004{col 43}{space 1}    0.16{col 52}{space 3}0.873{col 60}{space 4}-.5096375{col 73}{space 3} .6000125
{txt}{space 15}DE  {c |}{col 20}{res}{space 2} .1976579{col 32}{space 2} .2405696{col 43}{space 1}    0.82{col 52}{space 3}0.412{col 60}{space 4}-.2761548{col 73}{space 3} .6714706
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2} .3091234{col 32}{space 2} .2495681{col 43}{space 1}    1.24{col 52}{space 3}0.217{col 60}{space 4} -.182411{col 73}{space 3} .8006578
{txt}full time student  {c |}{col 20}{res}{space 2}-.1502432{col 32}{space 2} .3156451{col 43}{space 1}   -0.48{col 52}{space 3}0.635{col 60}{space 4}-.7719233{col 73}{space 3} .4714368
{txt}{space 10}retired  {c |}{col 20}{res}{space 2} .0909701{col 32}{space 2} .2548243{col 43}{space 1}    0.36{col 52}{space 3}0.721{col 60}{space 4}-.4109164{col 73}{space 3} .5928566
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2}-.4031636{col 32}{space 2} .3529202{col 43}{space 1}   -1.14{col 52}{space 3}0.254{col 60}{space 4}-1.098256{col 73}{space 3} .2919294
{txt}{space 6}not working  {c |}{col 20}{res}{space 2} .0792717{col 32}{space 2} .4139671{col 43}{space 1}    0.19{col 52}{space 3}0.848{col 60}{space 4} -.736057{col 73}{space 3} .8946005
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2} .3828223{col 32}{space 2} .8385395{col 43}{space 1}    0.46{col 52}{space 3}0.648{col 60}{space 4}-1.268715{col 73}{space 3} 2.034359
{txt}{space 7}Bidentity_2 {c |}{col 20}{res}{space 2} .4819243{col 32}{space 2} .1272677{col 43}{space 1}    3.79{col 52}{space 3}0.000{col 60}{space 4} .2312653{col 73}{space 3} .7325832
{txt}{space 9}retroecon {c |}{col 20}{res}{space 2} .0192245{col 32}{space 2} .0884236{col 43}{space 1}    0.22{col 52}{space 3}0.828{col 60}{space 4}-.1549295{col 73}{space 3} .1933785
{txt}{space 10}retrofin {c |}{col 20}{res}{space 2}-.2754203{col 32}{space 2} .0943796{col 43}{space 1}   -2.92{col 52}{space 3}0.004{col 60}{space 4}-.4613045{col 73}{space 3}-.0895362
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .4461311{col 32}{space 2} .1331891{col 43}{space 1}    3.35{col 52}{space 3}0.001{col 60}{space 4} .1837939{col 73}{space 3} .7084683
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .3361319{col 32}{space 2} .3219923{col 43}{space 1}    1.04{col 52}{space 3}0.298{col 60}{space 4}-.2982238{col 73}{space 3} .9704877
{txt}{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
             /cut1 {c |}{col 20}{res}{space 2}-.6138994{col 32}{space 2} 1.493318{col 43}{space 1}   -0.41{col 52}{space 3}0.681{col 60}{space 4}-3.555054{col 73}{space 3} 2.327255
{txt}             /cut2 {c |}{col 20}{res}{space 2} .0114994{col 32}{space 2} 1.501276{col 43}{space 1}    0.01{col 52}{space 3}0.994{col 60}{space 4} -2.94533{col 73}{space 3} 2.968329
{txt}             /cut3 {c |}{col 20}{res}{space 2} .9022298{col 32}{space 2} 1.510513{col 43}{space 1}    0.60{col 52}{space 3}0.551{col 60}{space 4}-2.072793{col 73}{space 3} 3.877252
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. * decoupled
. mi estimate: svy: oprobit threat4 female Age edu_age i.SocialGrade i.work_status UKborn Bidentity_2 retroecon retrofin authvalues selfest if treatment==0  
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Ordered probit regression{col 49}Number of obs{col 67}= {res}       437

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 438.376718
{txt}{col 1}Number of PSUs{col 19}= {res}      437
{txt}{col 49}Average RVI{col 67}= {res}    0.0053
{txt}{col 49}Largest FMI{col 67}= {res}    0.0303
{txt}{col 49}Complete DF{col 67}= {res}       436
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    404.02
{txt}{col 49}        avg{col 67}= {res}    429.74
{txt}{col 49}        max{col 67}= {res}    433.77
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  17{txt},{res}  433.9{txt}){col 67}= {res}      7.07
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           threat4{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}female {c |}{col 20}{res}{space 2} .1340614{col 32}{space 2}  .118676{col 43}{space 1}    1.13{col 52}{space 3}0.259{col 60}{space 4}-.0991919{col 73}{space 3} .3673147
{txt}{space 15}Age {c |}{col 20}{res}{space 2} .0061343{col 32}{space 2} .0055271{col 43}{space 1}    1.11{col 52}{space 3}0.268{col 60}{space 4}-.0047291{col 73}{space 3} .0169977
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.1034973{col 32}{space 2} .0388098{col 43}{space 1}   -2.67{col 52}{space 3}0.008{col 60}{space 4}-.1797765{col 73}{space 3}-.0272182
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2} .2658792{col 32}{space 2} .1376095{col 43}{space 1}    1.93{col 52}{space 3}0.054{col 60}{space 4}-.0045854{col 73}{space 3} .5363439
{txt}{space 15}C2  {c |}{col 20}{res}{space 2} .0187579{col 32}{space 2} .2001177{col 43}{space 1}    0.09{col 52}{space 3}0.925{col 60}{space 4}-.3745645{col 73}{space 3} .4120804
{txt}{space 15}DE  {c |}{col 20}{res}{space 2} .3606859{col 32}{space 2} .1740458{col 43}{space 1}    2.07{col 52}{space 3}0.039{col 60}{space 4} .0186062{col 73}{space 3} .7027656
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2}-.1131599{col 32}{space 2} .1783985{col 43}{space 1}   -0.63{col 52}{space 3}0.526{col 60}{space 4}-.4637931{col 73}{space 3} .2374733
{txt}full time student  {c |}{col 20}{res}{space 2}-.5781354{col 32}{space 2} .3541425{col 43}{space 1}   -1.63{col 52}{space 3}0.103{col 60}{space 4}-1.274184{col 73}{space 3} .1179132
{txt}{space 10}retired  {c |}{col 20}{res}{space 2}-.1089674{col 32}{space 2} .1888336{col 43}{space 1}   -0.58{col 52}{space 3}0.564{col 60}{space 4}-.4801107{col 73}{space 3}  .262176
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2}-.4114983{col 32}{space 2} .2660419{col 43}{space 1}   -1.55{col 52}{space 3}0.123{col 60}{space 4}-.9343951{col 73}{space 3} .1113985
{txt}{space 6}not working  {c |}{col 20}{res}{space 2}-.0885131{col 32}{space 2} .2152624{col 43}{space 1}   -0.41{col 52}{space 3}0.681{col 60}{space 4}-.5116118{col 73}{space 3} .3345856
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2} 1.629221{col 32}{space 2} .3342982{col 43}{space 1}    4.87{col 52}{space 3}0.000{col 60}{space 4} .9721714{col 73}{space 3}  2.28627
{txt}{space 7}Bidentity_2 {c |}{col 20}{res}{space 2} .4706919{col 32}{space 2} .1124081{col 43}{space 1}    4.19{col 52}{space 3}0.000{col 60}{space 4} .2497586{col 73}{space 3} .6916253
{txt}{space 9}retroecon {c |}{col 20}{res}{space 2} .0078013{col 32}{space 2} .0711278{col 43}{space 1}    0.11{col 52}{space 3}0.913{col 60}{space 4} -.131997{col 73}{space 3} .1475996
{txt}{space 10}retrofin {c |}{col 20}{res}{space 2} -.035483{col 32}{space 2} .0757131{col 43}{space 1}   -0.47{col 52}{space 3}0.640{col 60}{space 4}-.1842937{col 73}{space 3} .1133278
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .2586222{col 32}{space 2} .1160444{col 43}{space 1}    2.23{col 52}{space 3}0.026{col 60}{space 4} .0305012{col 73}{space 3} .4867432
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .5745074{col 32}{space 2}  .241722{col 43}{space 1}    2.38{col 52}{space 3}0.018{col 60}{space 4} .0993175{col 73}{space 3} 1.049697
{txt}{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
             /cut1 {c |}{col 20}{res}{space 2} .5595737{col 32}{space 2} 1.132847{col 43}{space 1}    0.49{col 52}{space 3}0.622{col 60}{space 4}-1.667024{col 73}{space 3} 2.786171
{txt}             /cut2 {c |}{col 20}{res}{space 2} 1.519618{col 32}{space 2}  1.14278{col 43}{space 1}    1.33{col 52}{space 3}0.184{col 60}{space 4}-.7265017{col 73}{space 3} 3.765738
{txt}             /cut3 {c |}{col 20}{res}{space 2} 2.675914{col 32}{space 2} 1.144949{col 43}{space 1}    2.34{col 52}{space 3}0.020{col 60}{space 4} .4255289{col 73}{space 3}   4.9263
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. * coupled
. mi estimate: svy: oprobit threat5 female Age edu_age i.SocialGrade i.work_status UKborn Bidentity_2 retroecon retrofin authvalues selfest if treatment==1 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Ordered probit regression{col 49}Number of obs{col 67}= {res}       252

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 252.838098
{txt}{col 1}Number of PSUs{col 19}= {res}      252
{txt}{col 49}Average RVI{col 67}= {res}    0.0030
{txt}{col 49}Largest FMI{col 67}= {res}    0.0192
{txt}{col 49}Complete DF{col 67}= {res}       251
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    241.98
{txt}{col 49}        avg{col 67}= {res}    248.05
{txt}{col 49}        max{col 67}= {res}    248.94
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  17{txt},{res}  249.0{txt}){col 67}= {res}      4.05
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           threat5{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}female {c |}{col 20}{res}{space 2} .2154854{col 32}{space 2} .1495693{col 43}{space 1}    1.44{col 52}{space 3}0.151{col 60}{space 4}-.0790994{col 73}{space 3} .5100703
{txt}{space 15}Age {c |}{col 20}{res}{space 2} .0024703{col 32}{space 2} .0078039{col 43}{space 1}    0.32{col 52}{space 3}0.752{col 60}{space 4}   -.0129{col 73}{space 3} .0178406
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.1034568{col 32}{space 2} .0464614{col 43}{space 1}   -2.23{col 52}{space 3}0.027{col 60}{space 4} -.194965{col 73}{space 3}-.0119486
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2}-.0207814{col 32}{space 2} .1787323{col 43}{space 1}   -0.12{col 52}{space 3}0.908{col 60}{space 4}-.3728064{col 73}{space 3} .3312436
{txt}{space 15}C2  {c |}{col 20}{res}{space 2} .1141144{col 32}{space 2} .2755309{col 43}{space 1}    0.41{col 52}{space 3}0.679{col 60}{space 4}-.4285576{col 73}{space 3} .6567865
{txt}{space 15}DE  {c |}{col 20}{res}{space 2} .0824692{col 32}{space 2} .2339582{col 43}{space 1}    0.35{col 52}{space 3}0.725{col 60}{space 4}-.3783226{col 73}{space 3} .5432609
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2}  .212543{col 32}{space 2} .2557263{col 43}{space 1}    0.83{col 52}{space 3}0.407{col 60}{space 4}-.2911207{col 73}{space 3} .7162068
{txt}full time student  {c |}{col 20}{res}{space 2} .2271745{col 32}{space 2} .3438715{col 43}{space 1}    0.66{col 52}{space 3}0.509{col 60}{space 4}-.4501077{col 73}{space 3} .9044567
{txt}{space 10}retired  {c |}{col 20}{res}{space 2} .0159477{col 32}{space 2} .2713195{col 43}{space 1}    0.06{col 52}{space 3}0.953{col 60}{space 4} -.518427{col 73}{space 3} .5503225
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2}-.2787064{col 32}{space 2} .3528738{col 43}{space 1}   -0.79{col 52}{space 3}0.430{col 60}{space 4}-.9737086{col 73}{space 3} .4162958
{txt}{space 6}not working  {c |}{col 20}{res}{space 2} .2311607{col 32}{space 2} .2902128{col 43}{space 1}    0.80{col 52}{space 3}0.426{col 60}{space 4}-.3404307{col 73}{space 3}  .802752
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2} .7184193{col 32}{space 2} .6296037{col 43}{space 1}    1.14{col 52}{space 3}0.255{col 60}{space 4}-.5216103{col 73}{space 3} 1.958449
{txt}{space 7}Bidentity_2 {c |}{col 20}{res}{space 2} .3717403{col 32}{space 2} .1211352{col 43}{space 1}    3.07{col 52}{space 3}0.002{col 60}{space 4} .1331593{col 73}{space 3} .6103214
{txt}{space 9}retroecon {c |}{col 20}{res}{space 2} .0396896{col 32}{space 2} .0781216{col 43}{space 1}    0.51{col 52}{space 3}0.612{col 60}{space 4}-.1141747{col 73}{space 3}  .193554
{txt}{space 10}retrofin {c |}{col 20}{res}{space 2}-.2479933{col 32}{space 2}  .094572{col 43}{space 1}   -2.62{col 52}{space 3}0.009{col 60}{space 4}-.4342566{col 73}{space 3}-.0617301
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .6034481{col 32}{space 2} .1414912{col 43}{space 1}    4.26{col 52}{space 3}0.000{col 60}{space 4} .3247364{col 73}{space 3} .8821597
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .3342233{col 32}{space 2} .3269335{col 43}{space 1}    1.02{col 52}{space 3}0.308{col 60}{space 4}-.3097468{col 73}{space 3} .9781934
{txt}{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
             /cut1 {c |}{col 20}{res}{space 2} .1615772{col 32}{space 2} 1.380743{col 43}{space 1}    0.12{col 52}{space 3}0.907{col 60}{space 4}-2.557867{col 73}{space 3} 2.881022
{txt}             /cut2 {c |}{col 20}{res}{space 2} 1.173236{col 32}{space 2} 1.392776{col 43}{space 1}    0.84{col 52}{space 3}0.400{col 60}{space 4}-1.569909{col 73}{space 3}  3.91638
{txt}             /cut3 {c |}{col 20}{res}{space 2} 2.144293{col 32}{space 2} 1.402833{col 43}{space 1}    1.53{col 52}{space 3}0.128{col 60}{space 4}-.6186605{col 73}{space 3} 4.907247
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. * decoupled
. mi estimate: svy: oprobit threat5 female Age edu_age i.SocialGrade i.work_status UKborn Bidentity_2 retroecon retrofin authvalues selfest if treatment==0 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Ordered probit regression{col 49}Number of obs{col 67}= {res}       441

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 442.030845
{txt}{col 1}Number of PSUs{col 19}= {res}      441
{txt}{col 49}Average RVI{col 67}= {res}    0.0153
{txt}{col 49}Largest FMI{col 67}= {res}    0.1738
{txt}{col 49}Complete DF{col 67}= {res}       440
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    170.15
{txt}{col 49}        avg{col 67}= {res}    420.82
{txt}{col 49}        max{col 67}= {res}    437.39
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  17{txt},{res}  437.5{txt}){col 67}= {res}      6.26
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           threat5{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}female {c |}{col 20}{res}{space 2}  .168352{col 32}{space 2}  .127389{col 43}{space 1}    1.32{col 52}{space 3}0.187{col 60}{space 4}-.0820191{col 73}{space 3}  .418723
{txt}{space 15}Age {c |}{col 20}{res}{space 2}-.0022474{col 32}{space 2} .0055692{col 43}{space 1}   -0.40{col 52}{space 3}0.687{col 60}{space 4}-.0131941{col 73}{space 3} .0086994
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0314978{col 32}{space 2} .0391556{col 43}{space 1}   -0.80{col 52}{space 3}0.422{col 60}{space 4}-.1084561{col 73}{space 3} .0454605
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2}-.0518227{col 32}{space 2} .1628618{col 43}{space 1}   -0.32{col 52}{space 3}0.750{col 60}{space 4}-.3719131{col 73}{space 3} .2682677
{txt}{space 15}C2  {c |}{col 20}{res}{space 2} .1347614{col 32}{space 2} .1729275{col 43}{space 1}    0.78{col 52}{space 3}0.436{col 60}{space 4}-.2051115{col 73}{space 3} .4746342
{txt}{space 15}DE  {c |}{col 20}{res}{space 2} .1843504{col 32}{space 2} .1734618{col 43}{space 1}    1.06{col 52}{space 3}0.288{col 60}{space 4}-.1565722{col 73}{space 3} .5252729
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2}-.3153299{col 32}{space 2} .1727732{col 43}{space 1}   -1.83{col 52}{space 3}0.069{col 60}{space 4}-.6548992{col 73}{space 3} .0242394
{txt}full time student  {c |}{col 20}{res}{space 2} .0433112{col 32}{space 2} .3550467{col 43}{space 1}    0.12{col 52}{space 3}0.903{col 60}{space 4}-.6544986{col 73}{space 3} .7411209
{txt}{space 10}retired  {c |}{col 20}{res}{space 2}-.5067314{col 32}{space 2} .1932538{col 43}{space 1}   -2.62{col 52}{space 3}0.009{col 60}{space 4}-.8865528{col 73}{space 3}-.1269099
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2} .0043387{col 32}{space 2} .3802001{col 43}{space 1}    0.01{col 52}{space 3}0.991{col 60}{space 4}-.7429132{col 73}{space 3} .7515906
{txt}{space 6}not working  {c |}{col 20}{res}{space 2}-.5440843{col 32}{space 2} .1982703{col 43}{space 1}   -2.74{col 52}{space 3}0.006{col 60}{space 4}-.9337728{col 73}{space 3}-.1543958
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2} .1629736{col 32}{space 2}  .296796{col 43}{space 1}    0.55{col 52}{space 3}0.583{col 60}{space 4}-.4203506{col 73}{space 3} .7462978
{txt}{space 7}Bidentity_2 {c |}{col 20}{res}{space 2} -.055225{col 32}{space 2} .1053406{col 43}{space 1}   -0.52{col 52}{space 3}0.600{col 60}{space 4}-.2622619{col 73}{space 3} .1518119
{txt}{space 9}retroecon {c |}{col 20}{res}{space 2}-.5755834{col 32}{space 2} .0895283{col 43}{space 1}   -6.43{col 52}{space 3}0.000{col 60}{space 4}-.7515446{col 73}{space 3}-.3996223
{txt}{space 10}retrofin {c |}{col 20}{res}{space 2}-.2338844{col 32}{space 2} .0744117{col 43}{space 1}   -3.14{col 52}{space 3}0.002{col 60}{space 4}-.3801341{col 73}{space 3}-.0876348
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2}  .153162{col 32}{space 2} .1102361{col 43}{space 1}    1.39{col 52}{space 3}0.165{col 60}{space 4}-.0635202{col 73}{space 3} .3698442
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .6268952{col 32}{space 2} .2997378{col 43}{space 1}    2.09{col 52}{space 3}0.038{col 60}{space 4} .0352117{col 73}{space 3} 1.218579
{txt}{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
             /cut1 {c |}{col 20}{res}{space 2}-4.495873{col 32}{space 2} 1.211588{col 43}{space 1}   -3.71{col 52}{space 3}0.000{col 60}{space 4} -6.87721{col 73}{space 3}-2.114536
{txt}             /cut2 {c |}{col 20}{res}{space 2} -3.35485{col 32}{space 2}  1.16302{col 43}{space 1}   -2.88{col 52}{space 3}0.004{col 60}{space 4}-5.640755{col 73}{space 3}-1.068946
{txt}             /cut3 {c |}{col 20}{res}{space 2}-1.306734{col 32}{space 2} 1.146718{col 43}{space 1}   -1.14{col 52}{space 3}0.255{col 60}{space 4}-3.560623{col 73}{space 3} .9471553
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. 
. *********************************************************************
. * TABLE A.7A IN THE APPENDIX:
. *       Predictors of Group Hostility under Coupled (C) and Decoupled (D) Conditions, 2011; 
. *       Threats Entered Individually
. * FIGURE A.1A IN THE APPENDIX:
. *       Unstandardized OLS Coefficient Estimates and 95% Confidence Intervals of the Impact of Coupled (C) 
. *       and Decoupled (D) Threats on Group Hostility, 2011; Threats Entered Individually
. **      NOTE: for significance test see code for FIGURE A.1B below 
. * FIGURE 1 IN THE PAPER (2011 estimates):
. *       Unstandardized OLS Coefficient Estimates and 95% Confidence Intervals of the Impact of Threats
. *       on Group Hostility; Threats Entered Individually
. **      NOTE: for significance test of difference between 2011 and 2016 estimates, 
. **      see code for FIGURE 1 below
. *********************************************************************
. 
. * coupled
. mi estimate: svy: reg GHblack threat1 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest if treatment==1 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       230

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 229.513033
{txt}{col 1}Number of PSUs{col 19}= {res}      230
{txt}{col 49}Average RVI{col 67}= {res}    0.1090
{txt}{col 49}Largest FMI{col 67}= {res}    0.1567
{txt}{col 49}Complete DF{col 67}= {res}       229
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    129.41
{txt}{col 49}        avg{col 67}= {res}    181.77
{txt}{col 49}        max{col 67}= {res}    224.90
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  15{txt},{res}  223.0{txt}){col 67}= {res}     15.84
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           GHblack{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat1 {c |}{col 20}{res}{space 2} .3246079{col 32}{space 2} .0425792{col 43}{space 1}    7.62{col 52}{space 3}0.000{col 60}{space 4} .2406697{col 73}{space 3} .4085461
{txt}{space 12}female {c |}{col 20}{res}{space 2} -.010836{col 32}{space 2} .0747886{col 43}{space 1}   -0.14{col 52}{space 3}0.885{col 60}{space 4}-.1584645{col 73}{space 3} .1367924
{txt}{space 15}Age {c |}{col 20}{res}{space 2} .0037432{col 32}{space 2} .0035393{col 43}{space 1}    1.06{col 52}{space 3}0.292{col 60}{space 4}-.0032572{col 73}{space 3} .0107436
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0341303{col 32}{space 2} .0200429{col 43}{space 1}   -1.70{col 52}{space 3}0.090{col 60}{space 4}-.0736715{col 73}{space 3}  .005411
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2}-.0279914{col 32}{space 2} .0784952{col 43}{space 1}   -0.36{col 52}{space 3}0.722{col 60}{space 4}-.1830667{col 73}{space 3}  .127084
{txt}{space 15}C2  {c |}{col 20}{res}{space 2}-.1529702{col 32}{space 2}  .156294{col 43}{space 1}   -0.98{col 52}{space 3}0.329{col 60}{space 4}-.4610478{col 73}{space 3} .1551073
{txt}{space 15}DE  {c |}{col 20}{res}{space 2}-.2155982{col 32}{space 2} .0948325{col 43}{space 1}   -2.27{col 52}{space 3}0.024{col 60}{space 4}-.4030362{col 73}{space 3}-.0281602
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2} .0509397{col 32}{space 2} .1001451{col 43}{space 1}    0.51{col 52}{space 3}0.612{col 60}{space 4}-.1468363{col 73}{space 3} .2487157
{txt}full time student  {c |}{col 20}{res}{space 2}-.1806818{col 32}{space 2} .2875225{col 43}{space 1}   -0.63{col 52}{space 3}0.530{col 60}{space 4}-.7475493{col 73}{space 3} .3861857
{txt}{space 10}retired  {c |}{col 20}{res}{space 2} .0565943{col 32}{space 2} .1057112{col 43}{space 1}    0.54{col 52}{space 3}0.593{col 60}{space 4}-.1519725{col 73}{space 3} .2651611
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2} -.223751{col 32}{space 2} .1877312{col 43}{space 1}   -1.19{col 52}{space 3}0.235{col 60}{space 4}-.5936881{col 73}{space 3}  .146186
{txt}{space 6}not working  {c |}{col 20}{res}{space 2} .0317761{col 32}{space 2} .1281948{col 43}{space 1}    0.25{col 52}{space 3}0.805{col 60}{space 4}-.2218528{col 73}{space 3}  .285405
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2} .5001705{col 32}{space 2} .1442973{col 43}{space 1}    3.47{col 52}{space 3}0.001{col 60}{space 4} .2157451{col 73}{space 3} .7845958
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .1833838{col 32}{space 2} .0645071{col 43}{space 1}    2.84{col 52}{space 3}0.005{col 60}{space 4} .0561642{col 73}{space 3} .3106035
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .1907162{col 32}{space 2} .1340662{col 43}{space 1}    1.42{col 52}{space 3}0.156{col 60}{space 4}-.0735782{col 73}{space 3} .4550105
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 1.012661{col 32}{space 2} .4846942{col 43}{space 1}    2.09{col 52}{space 3}0.038{col 60}{space 4} .0560863{col 73}{space 3} 1.969236
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHblack threat2 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest if treatment==1 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       231

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 230.513033
{txt}{col 1}Number of PSUs{col 19}= {res}      231
{txt}{col 49}Average RVI{col 67}= {res}    0.0947
{txt}{col 49}Largest FMI{col 67}= {res}    0.1631
{txt}{col 49}Complete DF{col 67}= {res}       230
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    125.77
{txt}{col 49}        avg{col 67}= {res}    189.19
{txt}{col 49}        max{col 67}= {res}    226.64
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  15{txt},{res}  224.6{txt}){col 67}= {res}     11.73
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           GHblack{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat2 {c |}{col 20}{res}{space 2} .2411604{col 32}{space 2} .0524176{col 43}{space 1}    4.60{col 52}{space 3}0.000{col 60}{space 4} .1377978{col 73}{space 3}  .344523
{txt}{space 12}female {c |}{col 20}{res}{space 2}-.0773502{col 32}{space 2} .0768411{col 43}{space 1}   -1.01{col 52}{space 3}0.315{col 60}{space 4}-.2289986{col 73}{space 3} .0742982
{txt}{space 15}Age {c |}{col 20}{res}{space 2} .0032683{col 32}{space 2} .0039742{col 43}{space 1}    0.82{col 52}{space 3}0.412{col 60}{space 4}-.0045833{col 73}{space 3} .0111199
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0322072{col 32}{space 2} .0221804{col 43}{space 1}   -1.45{col 52}{space 3}0.148{col 60}{space 4}-.0759453{col 73}{space 3} .0115308
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2}-.0383502{col 32}{space 2} .0888632{col 43}{space 1}   -0.43{col 52}{space 3}0.667{col 60}{space 4}-.2137501{col 73}{space 3} .1370497
{txt}{space 15}C2  {c |}{col 20}{res}{space 2}-.1698707{col 32}{space 2} .1472756{col 43}{space 1}   -1.15{col 52}{space 3}0.250{col 60}{space 4}-.4601781{col 73}{space 3} .1204367
{txt}{space 15}DE  {c |}{col 20}{res}{space 2}-.2168291{col 32}{space 2} .1150978{col 43}{space 1}   -1.88{col 52}{space 3}0.061{col 60}{space 4}-.4439795{col 73}{space 3} .0103212
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2}-.0199087{col 32}{space 2} .1163837{col 43}{space 1}   -0.17{col 52}{space 3}0.864{col 60}{space 4}-.2495459{col 73}{space 3} .2097284
{txt}full time student  {c |}{col 20}{res}{space 2}-.1244458{col 32}{space 2}  .214899{col 43}{space 1}   -0.58{col 52}{space 3}0.563{col 60}{space 4}-.5484933{col 73}{space 3} .2996017
{txt}{space 10}retired  {c |}{col 20}{res}{space 2} .1040479{col 32}{space 2} .1284598{col 43}{space 1}    0.81{col 52}{space 3}0.419{col 60}{space 4}-.1492795{col 73}{space 3} .3573753
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2}-.2444235{col 32}{space 2} .2175265{col 43}{space 1}   -1.12{col 52}{space 3}0.262{col 60}{space 4}-.6730565{col 73}{space 3} .1842095
{txt}{space 6}not working  {c |}{col 20}{res}{space 2} .0851582{col 32}{space 2} .1296535{col 43}{space 1}    0.66{col 52}{space 3}0.513{col 60}{space 4}-.1714268{col 73}{space 3} .3417432
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2} .5801712{col 32}{space 2} .1200981{col 43}{space 1}    4.83{col 52}{space 3}0.000{col 60}{space 4} .3434218{col 73}{space 3} .8169205
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .2146295{col 32}{space 2} .0745142{col 43}{space 1}    2.88{col 52}{space 3}0.004{col 60}{space 4} .0677092{col 73}{space 3} .3615497
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .1458766{col 32}{space 2} .1568329{col 43}{space 1}    0.93{col 52}{space 3}0.353{col 60}{space 4}-.1632589{col 73}{space 3}  .455012
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 1.044811{col 32}{space 2} .5639588{col 43}{space 1}    1.85{col 52}{space 3}0.065{col 60}{space 4}-.0673067{col 73}{space 3} 2.156928
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHblack threat3 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest if treatment==1 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       232

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 231.513033
{txt}{col 1}Number of PSUs{col 19}= {res}      232
{txt}{col 49}Average RVI{col 67}= {res}    0.0843
{txt}{col 49}Largest FMI{col 67}= {res}    0.1715
{txt}{col 49}Complete DF{col 67}= {res}       231
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    121.10
{txt}{col 49}        avg{col 67}= {res}    193.49
{txt}{col 49}        max{col 67}= {res}    227.14
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  15{txt},{res}  226.1{txt}){col 67}= {res}     10.48
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           GHblack{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat3 {c |}{col 20}{res}{space 2} .2069793{col 32}{space 2} .0489141{col 43}{space 1}    4.23{col 52}{space 3}0.000{col 60}{space 4} .1105928{col 73}{space 3} .3033657
{txt}{space 12}female {c |}{col 20}{res}{space 2}-.0482639{col 32}{space 2} .0794927{col 43}{space 1}   -0.61{col 52}{space 3}0.545{col 60}{space 4}-.2051086{col 73}{space 3} .1085809
{txt}{space 15}Age {c |}{col 20}{res}{space 2} .0037173{col 32}{space 2} .0038056{col 43}{space 1}    0.98{col 52}{space 3}0.330{col 60}{space 4} -.003802{col 73}{space 3} .0112366
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0245374{col 32}{space 2} .0222005{col 43}{space 1}   -1.11{col 52}{space 3}0.270{col 60}{space 4}-.0683128{col 73}{space 3}  .019238
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2}-.0058636{col 32}{space 2}  .088908{col 43}{space 1}   -0.07{col 52}{space 3}0.947{col 60}{space 4}-.1813299{col 73}{space 3} .1696027
{txt}{space 15}C2  {c |}{col 20}{res}{space 2}-.1187996{col 32}{space 2} .1611768{col 43}{space 1}   -0.74{col 52}{space 3}0.462{col 60}{space 4}-.4364792{col 73}{space 3}   .19888
{txt}{space 15}DE  {c |}{col 20}{res}{space 2}-.1962185{col 32}{space 2} .1133183{col 43}{space 1}   -1.73{col 52}{space 3}0.085{col 60}{space 4}-.4198716{col 73}{space 3} .0274346
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2} .0078338{col 32}{space 2} .1116343{col 43}{space 1}    0.07{col 52}{space 3}0.944{col 60}{space 4}-.2124379{col 73}{space 3} .2281055
{txt}full time student  {c |}{col 20}{res}{space 2}-.1833817{col 32}{space 2} .2621574{col 43}{space 1}   -0.70{col 52}{space 3}0.485{col 60}{space 4} -.700326{col 73}{space 3} .3335625
{txt}{space 10}retired  {c |}{col 20}{res}{space 2} .0584812{col 32}{space 2} .1218496{col 43}{space 1}    0.48{col 52}{space 3}0.632{col 60}{space 4}-.1817943{col 73}{space 3} .2987568
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2}-.2016331{col 32}{space 2} .2086096{col 43}{space 1}   -0.97{col 52}{space 3}0.335{col 60}{space 4}-.6126905{col 73}{space 3} .2094243
{txt}{space 6}not working  {c |}{col 20}{res}{space 2} .1085047{col 32}{space 2} .1293865{col 43}{space 1}    0.84{col 52}{space 3}0.403{col 60}{space 4}-.1476479{col 73}{space 3} .3646572
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2} .5409804{col 32}{space 2} .1190497{col 43}{space 1}    4.54{col 52}{space 3}0.000{col 60}{space 4} .3062916{col 73}{space 3} .7756692
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .2473629{col 32}{space 2} .0747397{col 43}{space 1}    3.31{col 52}{space 3}0.001{col 60}{space 4} .1000603{col 73}{space 3} .3946655
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .2668728{col 32}{space 2} .1570651{col 43}{space 1}    1.70{col 52}{space 3}0.091{col 60}{space 4}-.0426787{col 73}{space 3} .5764243
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} .8401579{col 32}{space 2} .5471581{col 43}{space 1}    1.54{col 52}{space 3}0.126{col 60}{space 4}-.2390095{col 73}{space 3} 1.919325
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHblack threat4 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest if treatment==1 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       230

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 229.715427
{txt}{col 1}Number of PSUs{col 19}= {res}      230
{txt}{col 49}Average RVI{col 67}= {res}    0.0869
{txt}{col 49}Largest FMI{col 67}= {res}    0.1642
{txt}{col 49}Complete DF{col 67}= {res}       229
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    124.79
{txt}{col 49}        avg{col 67}= {res}    192.55
{txt}{col 49}        max{col 67}= {res}    225.47
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  15{txt},{res}  224.0{txt}){col 67}= {res}      9.66
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           GHblack{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat4 {c |}{col 20}{res}{space 2}   .16192{col 32}{space 2} .0384974{col 43}{space 1}    4.21{col 52}{space 3}0.000{col 60}{space 4} .0860486{col 73}{space 3} .2377914
{txt}{space 12}female {c |}{col 20}{res}{space 2}-.0542656{col 32}{space 2} .0833777{col 43}{space 1}   -0.65{col 52}{space 3}0.516{col 60}{space 4}-.2187595{col 73}{space 3} .1102282
{txt}{space 15}Age {c |}{col 20}{res}{space 2}  .004968{col 32}{space 2} .0037265{col 43}{space 1}    1.33{col 52}{space 3}0.185{col 60}{space 4}-.0023968{col 73}{space 3} .0123328
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0256267{col 32}{space 2} .0222017{col 43}{space 1}   -1.15{col 52}{space 3}0.250{col 60}{space 4}-.0694143{col 73}{space 3} .0181609
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2}-.0049991{col 32}{space 2} .0909404{col 43}{space 1}   -0.05{col 52}{space 3}0.956{col 60}{space 4}-.1844823{col 73}{space 3} .1744842
{txt}{space 15}C2  {c |}{col 20}{res}{space 2}-.1253344{col 32}{space 2} .1644208{col 43}{space 1}   -0.76{col 52}{space 3}0.447{col 60}{space 4}-.4494135{col 73}{space 3} .1987447
{txt}{space 15}DE  {c |}{col 20}{res}{space 2}-.1657675{col 32}{space 2} .1188718{col 43}{space 1}   -1.39{col 52}{space 3}0.165{col 60}{space 4}-.4003621{col 73}{space 3}  .068827
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2}-.0276675{col 32}{space 2} .1151921{col 43}{space 1}   -0.24{col 52}{space 3}0.810{col 60}{space 4}-.2549664{col 73}{space 3} .1996314
{txt}full time student  {c |}{col 20}{res}{space 2} -.081681{col 32}{space 2} .3050429{col 43}{space 1}   -0.27{col 52}{space 3}0.789{col 60}{space 4}-.6830832{col 73}{space 3} .5197211
{txt}{space 10}retired  {c |}{col 20}{res}{space 2} .0091053{col 32}{space 2} .1222576{col 43}{space 1}    0.07{col 52}{space 3}0.941{col 60}{space 4}-.2319837{col 73}{space 3} .2501942
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2}-.1677051{col 32}{space 2} .1994051{col 43}{space 1}   -0.84{col 52}{space 3}0.401{col 60}{space 4}-.5606411{col 73}{space 3} .2252309
{txt}{space 6}not working  {c |}{col 20}{res}{space 2} .1108365{col 32}{space 2} .1297381{col 43}{space 1}    0.85{col 52}{space 3}0.395{col 60}{space 4}-.1459356{col 73}{space 3} .3676086
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2} .5720045{col 32}{space 2}  .127392{col 43}{space 1}    4.49{col 52}{space 3}0.000{col 60}{space 4} .3208987{col 73}{space 3} .8231103
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .2680465{col 32}{space 2} .0721833{col 43}{space 1}    3.71{col 52}{space 3}0.000{col 60}{space 4} .1257498{col 73}{space 3} .4103433
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .2110251{col 32}{space 2} .1577472{col 43}{space 1}    1.34{col 52}{space 3}0.182{col 60}{space 4}-.0998596{col 73}{space 3} .5219097
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} .8082575{col 32}{space 2} .5511232{col 43}{space 1}    1.47{col 52}{space 3}0.144{col 60}{space 4}-.2788579{col 73}{space 3} 1.895373
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHblack threat5 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest if treatment==1 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       231

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 230.757784
{txt}{col 1}Number of PSUs{col 19}= {res}      231
{txt}{col 49}Average RVI{col 67}= {res}    0.0958
{txt}{col 49}Largest FMI{col 67}= {res}    0.1714
{txt}{col 49}Complete DF{col 67}= {res}       230
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    120.80
{txt}{col 49}        avg{col 67}= {res}    188.42
{txt}{col 49}        max{col 67}= {res}    226.61
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  15{txt},{res}  224.4{txt}){col 67}= {res}     11.76
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           GHblack{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat5 {c |}{col 20}{res}{space 2}  .241675{col 32}{space 2} .0460378{col 43}{space 1}    5.25{col 52}{space 3}0.000{col 60}{space 4} .1509228{col 73}{space 3} .3324273
{txt}{space 12}female {c |}{col 20}{res}{space 2}-.1173479{col 32}{space 2} .0787412{col 43}{space 1}   -1.49{col 52}{space 3}0.138{col 60}{space 4}-.2726954{col 73}{space 3} .0379996
{txt}{space 15}Age {c |}{col 20}{res}{space 2}  .003574{col 32}{space 2} .0035798{col 43}{space 1}    1.00{col 52}{space 3}0.320{col 60}{space 4}-.0035082{col 73}{space 3} .0106561
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0252947{col 32}{space 2} .0205245{col 43}{space 1}   -1.23{col 52}{space 3}0.219{col 60}{space 4}-.0657729{col 73}{space 3} .0151834
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2}-.0169514{col 32}{space 2} .0879456{col 43}{space 1}   -0.19{col 52}{space 3}0.847{col 60}{space 4}  -.19054{col 73}{space 3} .1566371
{txt}{space 15}C2  {c |}{col 20}{res}{space 2}-.1610554{col 32}{space 2}   .16519{col 43}{space 1}   -0.97{col 52}{space 3}0.331{col 60}{space 4}-.4866406{col 73}{space 3} .1645297
{txt}{space 15}DE  {c |}{col 20}{res}{space 2}-.1446767{col 32}{space 2} .1070623{col 43}{space 1}   -1.35{col 52}{space 3}0.178{col 60}{space 4}-.3560708{col 73}{space 3} .0667175
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2}-.0292752{col 32}{space 2} .1081827{col 43}{space 1}   -0.27{col 52}{space 3}0.787{col 60}{space 4} -.242787{col 73}{space 3} .1842367
{txt}full time student  {c |}{col 20}{res}{space 2} -.181859{col 32}{space 2} .2849028{col 43}{space 1}   -0.64{col 52}{space 3}0.524{col 60}{space 4}-.7435765{col 73}{space 3} .3798585
{txt}{space 10}retired  {c |}{col 20}{res}{space 2}-.0032318{col 32}{space 2} .1151941{col 43}{space 1}   -0.03{col 52}{space 3}0.978{col 60}{space 4}-.2304338{col 73}{space 3} .2239702
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2}-.2189941{col 32}{space 2} .2024805{col 43}{space 1}   -1.08{col 52}{space 3}0.281{col 60}{space 4}-.6179794{col 73}{space 3} .1799912
{txt}{space 6}not working  {c |}{col 20}{res}{space 2} .0438827{col 32}{space 2} .1266362{col 43}{space 1}    0.35{col 52}{space 3}0.730{col 60}{space 4}-.2068313{col 73}{space 3} .2945968
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2} .5336038{col 32}{space 2} .1178897{col 43}{space 1}    4.53{col 52}{space 3}0.000{col 60}{space 4} .3012101{col 73}{space 3} .7659975
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .2093632{col 32}{space 2} .0719195{col 43}{space 1}    2.91{col 52}{space 3}0.004{col 60}{space 4} .0675683{col 73}{space 3}  .351158
{txt}{space 11}selfest {c |}{col 20}{res}{space 2}  .207927{col 32}{space 2} .1475832{col 43}{space 1}    1.41{col 52}{space 3}0.160{col 60}{space 4}-.0829431{col 73}{space 3}  .498797
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} .9169425{col 32}{space 2} .5106902{col 43}{space 1}    1.80{col 52}{space 3}0.074{col 60}{space 4}-.0905809{col 73}{space 3} 1.924466
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. mi estimate: svy: reg GHMus threat1 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest if treatment==1 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       229

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res}  228.29205
{txt}{col 1}Number of PSUs{col 19}= {res}      229
{txt}{col 49}Average RVI{col 67}= {res}    0.0967
{txt}{col 49}Largest FMI{col 67}= {res}    0.1865
{txt}{col 49}Complete DF{col 67}= {res}       228
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    111.62
{txt}{col 49}        avg{col 67}= {res}    178.23
{txt}{col 49}        max{col 67}= {res}    223.14
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  15{txt},{res}  222.4{txt}){col 67}= {res}     14.31
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}             GHMus{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat1 {c |}{col 20}{res}{space 2} .3212174{col 32}{space 2} .0453804{col 43}{space 1}    7.08{col 52}{space 3}0.000{col 60}{space 4} .2316064{col 73}{space 3} .4108285
{txt}{space 12}female {c |}{col 20}{res}{space 2} .0174683{col 32}{space 2} .0806045{col 43}{space 1}    0.22{col 52}{space 3}0.829{col 60}{space 4}-.1416256{col 73}{space 3} .1765622
{txt}{space 15}Age {c |}{col 20}{res}{space 2} .0013774{col 32}{space 2} .0036897{col 43}{space 1}    0.37{col 52}{space 3}0.709{col 60}{space 4}-.0059171{col 73}{space 3} .0086719
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0487046{col 32}{space 2} .0259285{col 43}{space 1}   -1.88{col 52}{space 3}0.062{col 60}{space 4}-.0998687{col 73}{space 3} .0024596
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2} .1191353{col 32}{space 2} .0986199{col 43}{space 1}    1.21{col 52}{space 3}0.229{col 60}{space 4}-.0754566{col 73}{space 3} .3137273
{txt}{space 15}C2  {c |}{col 20}{res}{space 2}-.0751021{col 32}{space 2} .1475399{col 43}{space 1}   -0.51{col 52}{space 3}0.611{col 60}{space 4} -.365866{col 73}{space 3} .2156617
{txt}{space 15}DE  {c |}{col 20}{res}{space 2} .0787418{col 32}{space 2} .1136987{col 43}{space 1}    0.69{col 52}{space 3}0.490{col 60}{space 4} -.146546{col 73}{space 3} .3040297
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2} .2166736{col 32}{space 2} .1404874{col 43}{space 1}    1.54{col 52}{space 3}0.125{col 60}{space 4}-.0607164{col 73}{space 3} .4940635
{txt}full time student  {c |}{col 20}{res}{space 2} -.012866{col 32}{space 2} .2268571{col 43}{space 1}   -0.06{col 52}{space 3}0.955{col 60}{space 4}-.4600951{col 73}{space 3} .4343631
{txt}{space 10}retired  {c |}{col 20}{res}{space 2} .0440309{col 32}{space 2}  .123699{col 43}{space 1}    0.36{col 52}{space 3}0.722{col 60}{space 4}-.2000088{col 73}{space 3} .2880707
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2} .0044329{col 32}{space 2} .1671948{col 43}{space 1}    0.03{col 52}{space 3}0.979{col 60}{space 4}-.3250832{col 73}{space 3} .3339489
{txt}{space 6}not working  {c |}{col 20}{res}{space 2} .0554386{col 32}{space 2} .1519698{col 43}{space 1}    0.36{col 52}{space 3}0.716{col 60}{space 4}-.2447677{col 73}{space 3} .3556449
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2}  .129408{col 32}{space 2} .2289067{col 43}{space 1}    0.57{col 52}{space 3}0.572{col 60}{space 4}-.3216875{col 73}{space 3} .5805036
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .2441014{col 32}{space 2} .0710145{col 43}{space 1}    3.44{col 52}{space 3}0.001{col 60}{space 4} .1038426{col 73}{space 3} .3843602
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .1803589{col 32}{space 2} .1450152{col 43}{space 1}    1.24{col 52}{space 3}0.215{col 60}{space 4}-.1058591{col 73}{space 3} .4665769
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 1.598926{col 32}{space 2}  .626617{col 43}{space 1}    2.55{col 52}{space 3}0.011{col 60}{space 4} .3631133{col 73}{space 3} 2.834738
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHMus threat2 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest if treatment==1 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       230

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res}  229.29205
{txt}{col 1}Number of PSUs{col 19}= {res}      230
{txt}{col 49}Average RVI{col 67}= {res}    0.0886
{txt}{col 49}Largest FMI{col 67}= {res}    0.1627
{txt}{col 49}Complete DF{col 67}= {res}       229
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    125.71
{txt}{col 49}        avg{col 67}= {res}    183.38
{txt}{col 49}        max{col 67}= {res}    223.96
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  15{txt},{res}  223.8{txt}){col 67}= {res}     12.47
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}             GHMus{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat2 {c |}{col 20}{res}{space 2} .3016362{col 32}{space 2} .0489542{col 43}{space 1}    6.16{col 52}{space 3}0.000{col 60}{space 4} .2049282{col 73}{space 3} .3983442
{txt}{space 12}female {c |}{col 20}{res}{space 2}-.0659161{col 32}{space 2} .0828613{col 43}{space 1}   -0.80{col 52}{space 3}0.427{col 60}{space 4}-.2295047{col 73}{space 3} .0976725
{txt}{space 15}Age {c |}{col 20}{res}{space 2}-.0001923{col 32}{space 2} .0039297{col 43}{space 1}   -0.05{col 52}{space 3}0.961{col 60}{space 4}-.0079577{col 73}{space 3} .0075731
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0501774{col 32}{space 2} .0269515{col 43}{space 1}   -1.86{col 52}{space 3}0.064{col 60}{space 4}-.1033357{col 73}{space 3} .0029809
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2}  .109824{col 32}{space 2} .1060608{col 43}{space 1}    1.04{col 52}{space 3}0.302{col 60}{space 4}-.0993845{col 73}{space 3} .3190325
{txt}{space 15}C2  {c |}{col 20}{res}{space 2}-.0805793{col 32}{space 2} .1300954{col 43}{space 1}   -0.62{col 52}{space 3}0.536{col 60}{space 4}-.3369747{col 73}{space 3} .1758162
{txt}{space 15}DE  {c |}{col 20}{res}{space 2} .0918898{col 32}{space 2} .1164948{col 43}{space 1}    0.79{col 52}{space 3}0.432{col 60}{space 4}-.1386553{col 73}{space 3} .3224348
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2} .1110571{col 32}{space 2} .1531424{col 43}{space 1}    0.73{col 52}{space 3}0.469{col 60}{space 4}-.1911221{col 73}{space 3} .4132363
{txt}full time student  {c |}{col 20}{res}{space 2} .0259097{col 32}{space 2} .1584966{col 43}{space 1}    0.16{col 52}{space 3}0.870{col 60}{space 4}-.2868309{col 73}{space 3} .3386503
{txt}{space 10}retired  {c |}{col 20}{res}{space 2} .0867927{col 32}{space 2} .1347603{col 43}{space 1}    0.64{col 52}{space 3}0.520{col 60}{space 4} -.179036{col 73}{space 3} .3526214
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2}-.0303661{col 32}{space 2} .1591055{col 43}{space 1}   -0.19{col 52}{space 3}0.849{col 60}{space 4}-.3439313{col 73}{space 3} .2831991
{txt}{space 6}not working  {c |}{col 20}{res}{space 2} .0898069{col 32}{space 2} .1579576{col 43}{space 1}    0.57{col 52}{space 3}0.570{col 60}{space 4}-.2221584{col 73}{space 3} .4017721
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2} .3096116{col 32}{space 2} .1453534{col 43}{space 1}    2.13{col 52}{space 3}0.034{col 60}{space 4} .0231762{col 73}{space 3} .5960469
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .2627178{col 32}{space 2} .0778073{col 43}{space 1}    3.38{col 52}{space 3}0.001{col 60}{space 4} .1091667{col 73}{space 3} .4162688
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .0759846{col 32}{space 2} .1531249{col 43}{space 1}    0.50{col 52}{space 3}0.620{col 60}{space 4}-.2259827{col 73}{space 3} .3779519
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 1.544685{col 32}{space 2} .6849507{col 43}{space 1}    2.26{col 52}{space 3}0.025{col 60}{space 4} .1943904{col 73}{space 3} 2.894979
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHMus threat3 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest if treatment==1 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       231

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res}  230.29205
{txt}{col 1}Number of PSUs{col 19}= {res}      231
{txt}{col 49}Average RVI{col 67}= {res}    0.0946
{txt}{col 49}Largest FMI{col 67}= {res}    0.1701
{txt}{col 49}Complete DF{col 67}= {res}       230
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    121.57
{txt}{col 49}        avg{col 67}= {res}    181.90
{txt}{col 49}        max{col 67}= {res}    223.11
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  15{txt},{res}  224.5{txt}){col 67}= {res}     13.39
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}             GHMus{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat3 {c |}{col 20}{res}{space 2} .3433762{col 32}{space 2} .0454974{col 43}{space 1}    7.55{col 52}{space 3}0.000{col 60}{space 4} .2536629{col 73}{space 3} .4330894
{txt}{space 12}female {c |}{col 20}{res}{space 2}-.0203399{col 32}{space 2} .0769109{col 43}{space 1}   -0.26{col 52}{space 3}0.792{col 60}{space 4}-.1722231{col 73}{space 3} .1315432
{txt}{space 15}Age {c |}{col 20}{res}{space 2} .0001129{col 32}{space 2} .0036523{col 43}{space 1}    0.03{col 52}{space 3}0.975{col 60}{space 4}-.0071059{col 73}{space 3} .0073316
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0264106{col 32}{space 2} .0250563{col 43}{space 1}   -1.05{col 52}{space 3}0.293{col 60}{space 4}-.0758584{col 73}{space 3} .0230372
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2} .1435722{col 32}{space 2} .0960487{col 43}{space 1}    1.49{col 52}{space 3}0.137{col 60}{space 4}-.0459371{col 73}{space 3} .3330816
{txt}{space 15}C2  {c |}{col 20}{res}{space 2}-.0335247{col 32}{space 2} .1325451{col 43}{space 1}   -0.25{col 52}{space 3}0.801{col 60}{space 4}-.2947267{col 73}{space 3} .2276774
{txt}{space 15}DE  {c |}{col 20}{res}{space 2} .1085482{col 32}{space 2} .1134262{col 43}{space 1}    0.96{col 52}{space 3}0.340{col 60}{space 4}-.1159983{col 73}{space 3} .3330948
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2} .1491227{col 32}{space 2} .1308104{col 43}{space 1}    1.14{col 52}{space 3}0.256{col 60}{space 4}-.1092498{col 73}{space 3} .4074952
{txt}full time student  {c |}{col 20}{res}{space 2}-.0917643{col 32}{space 2} .1706851{col 43}{space 1}   -0.54{col 52}{space 3}0.591{col 60}{space 4}-.4283965{col 73}{space 3} .2448679
{txt}{space 10}retired  {c |}{col 20}{res}{space 2} .0553235{col 32}{space 2} .1263851{col 43}{space 1}    0.44{col 52}{space 3}0.662{col 60}{space 4}-.1939966{col 73}{space 3} .3046435
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2} .0250766{col 32}{space 2} .1493544{col 43}{space 1}    0.17{col 52}{space 3}0.867{col 60}{space 4}-.2692909{col 73}{space 3} .3194441
{txt}{space 6}not working  {c |}{col 20}{res}{space 2} .1050007{col 32}{space 2}  .154325{col 43}{space 1}    0.68{col 52}{space 3}0.497{col 60}{space 4}-.1999118{col 73}{space 3} .4099132
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2} .1743239{col 32}{space 2} .1707123{col 43}{space 1}    1.02{col 52}{space 3}0.308{col 60}{space 4}-.1620909{col 73}{space 3} .5107386
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .2465978{col 32}{space 2} .0747618{col 43}{space 1}    3.30{col 52}{space 3}0.001{col 60}{space 4} .0991373{col 73}{space 3} .3940584
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .2324796{col 32}{space 2} .1445283{col 43}{space 1}    1.61{col 52}{space 3}0.109{col 60}{space 4}-.0526766{col 73}{space 3} .5176357
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 1.052944{col 32}{space 2}  .626777{col 43}{space 1}    1.68{col 52}{space 3}0.095{col 60}{space 4}-.1832217{col 73}{space 3} 2.289109
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHMus threat4 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest if treatment==1 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       231

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res}  230.29205
{txt}{col 1}Number of PSUs{col 19}= {res}      231
{txt}{col 49}Average RVI{col 67}= {res}    0.0819
{txt}{col 49}Largest FMI{col 67}= {res}    0.1350
{txt}{col 49}Complete DF{col 67}= {res}       230
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    144.09
{txt}{col 49}        avg{col 67}= {res}    191.14
{txt}{col 49}        max{col 67}= {res}    225.62
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  15{txt},{res}  225.2{txt}){col 67}= {res}     10.68
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}             GHMus{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat4 {c |}{col 20}{res}{space 2} .2619044{col 32}{space 2} .0466632{col 43}{space 1}    5.61{col 52}{space 3}0.000{col 60}{space 4} .1698722{col 73}{space 3} .3539366
{txt}{space 12}female {c |}{col 20}{res}{space 2}-.0464737{col 32}{space 2} .0848977{col 43}{space 1}   -0.55{col 52}{space 3}0.585{col 60}{space 4}-.2140369{col 73}{space 3} .1210896
{txt}{space 15}Age {c |}{col 20}{res}{space 2} .0012329{col 32}{space 2}  .004018{col 43}{space 1}    0.31{col 52}{space 3}0.759{col 60}{space 4} -.006703{col 73}{space 3} .0091687
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0336999{col 32}{space 2} .0259037{col 43}{space 1}   -1.30{col 52}{space 3}0.195{col 60}{space 4}-.0847819{col 73}{space 3} .0173821
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2}  .131595{col 32}{space 2} .0983436{col 43}{space 1}    1.34{col 52}{space 3}0.182{col 60}{space 4}-.0624072{col 73}{space 3} .3255972
{txt}{space 15}C2  {c |}{col 20}{res}{space 2}-.0499693{col 32}{space 2} .1497613{col 43}{space 1}   -0.33{col 52}{space 3}0.739{col 60}{space 4}-.3450889{col 73}{space 3} .2451502
{txt}{space 15}DE  {c |}{col 20}{res}{space 2} .1482471{col 32}{space 2} .1247146{col 43}{space 1}    1.19{col 52}{space 3}0.237{col 60}{space 4}-.0982594{col 73}{space 3} .3947536
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2} .1140423{col 32}{space 2} .1437532{col 43}{space 1}    0.79{col 52}{space 3}0.429{col 60}{space 4}-.1697556{col 73}{space 3} .3978402
{txt}full time student  {c |}{col 20}{res}{space 2} .0810789{col 32}{space 2} .2282347{col 43}{space 1}    0.36{col 52}{space 3}0.723{col 60}{space 4}-.3688556{col 73}{space 3} .5310134
{txt}{space 10}retired  {c |}{col 20}{res}{space 2}-.0112775{col 32}{space 2} .1296437{col 43}{space 1}   -0.09{col 52}{space 3}0.931{col 60}{space 4}-.2669814{col 73}{space 3} .2444264
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2} .0798848{col 32}{space 2} .1577741{col 43}{space 1}    0.51{col 52}{space 3}0.613{col 60}{space 4} -.231047{col 73}{space 3} .3908166
{txt}{space 6}not working  {c |}{col 20}{res}{space 2} .1198229{col 32}{space 2} .1710005{col 43}{space 1}    0.70{col 52}{space 3}0.484{col 60}{space 4}-.2177343{col 73}{space 3} .4573801
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2} .3200151{col 32}{space 2} .2000001{col 43}{space 1}    1.60{col 52}{space 3}0.111{col 60}{space 4} -.074092{col 73}{space 3} .7141222
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2}  .294443{col 32}{space 2} .0762145{col 43}{space 1}    3.86{col 52}{space 3}0.000{col 60}{space 4} .1441774{col 73}{space 3} .4447085
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .1596215{col 32}{space 2} .1552931{col 43}{space 1}    1.03{col 52}{space 3}0.305{col 60}{space 4}-.1468656{col 73}{space 3} .4661086
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 1.035322{col 32}{space 2} .6662958{col 43}{space 1}    1.55{col 52}{space 3}0.122{col 60}{space 4}   -.2781{col 73}{space 3} 2.348743
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHMus threat5 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest if treatment==1 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       231

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res}  230.29205
{txt}{col 1}Number of PSUs{col 19}= {res}      231
{txt}{col 49}Average RVI{col 67}= {res}    0.0941
{txt}{col 49}Largest FMI{col 67}= {res}    0.1781
{txt}{col 49}Complete DF{col 67}= {res}       230
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    116.92
{txt}{col 49}        avg{col 67}= {res}    184.03
{txt}{col 49}        max{col 67}= {res}    223.96
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  15{txt},{res}  224.5{txt}){col 67}= {res}     13.71
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}             GHMus{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat5 {c |}{col 20}{res}{space 2} .3385001{col 32}{space 2} .0471393{col 43}{space 1}    7.18{col 52}{space 3}0.000{col 60}{space 4}  .245561{col 73}{space 3} .4314391
{txt}{space 12}female {c |}{col 20}{res}{space 2}-.1124871{col 32}{space 2} .0775042{col 43}{space 1}   -1.45{col 52}{space 3}0.149{col 60}{space 4}-.2655029{col 73}{space 3} .0405287
{txt}{space 15}Age {c |}{col 20}{res}{space 2} .0010307{col 32}{space 2} .0038627{col 43}{space 1}    0.27{col 52}{space 3}0.790{col 60}{space 4}-.0066036{col 73}{space 3} .0086649
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0363741{col 32}{space 2}  .024715{col 43}{space 1}   -1.47{col 52}{space 3}0.143{col 60}{space 4}-.0851292{col 73}{space 3} .0123811
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2} .1244253{col 32}{space 2} .0954917{col 43}{space 1}    1.30{col 52}{space 3}0.194{col 60}{space 4}-.0639661{col 73}{space 3} .3128168
{txt}{space 15}C2  {c |}{col 20}{res}{space 2}-.0861334{col 32}{space 2} .1419357{col 43}{space 1}   -0.61{col 52}{space 3}0.545{col 60}{space 4}-.3658336{col 73}{space 3} .1935669
{txt}{space 15}DE  {c |}{col 20}{res}{space 2} .1428357{col 32}{space 2} .1114703{col 43}{space 1}    1.28{col 52}{space 3}0.203{col 60}{space 4}-.0779269{col 73}{space 3} .3635983
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2} .1091396{col 32}{space 2} .1467613{col 43}{space 1}    0.74{col 52}{space 3}0.458{col 60}{space 4}-.1805454{col 73}{space 3} .3988246
{txt}full time student  {c |}{col 20}{res}{space 2}-.0135319{col 32}{space 2} .2167287{col 43}{space 1}   -0.06{col 52}{space 3}0.950{col 60}{space 4}-.4408006{col 73}{space 3} .4137368
{txt}{space 10}retired  {c |}{col 20}{res}{space 2}-.0391118{col 32}{space 2} .1183444{col 43}{space 1}   -0.33{col 52}{space 3}0.741{col 60}{space 4}-.2726206{col 73}{space 3}  .194397
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2} .0364014{col 32}{space 2} .1681681{col 43}{space 1}    0.22{col 52}{space 3}0.829{col 60}{space 4}-.2950108{col 73}{space 3} .3678135
{txt}{space 6}not working  {c |}{col 20}{res}{space 2} .0583644{col 32}{space 2} .1549885{col 43}{space 1}    0.38{col 52}{space 3}0.707{col 60}{space 4}-.2477734{col 73}{space 3} .3645022
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2} .2463736{col 32}{space 2} .1487036{col 43}{space 1}    1.66{col 52}{space 3}0.099{col 60}{space 4}-.0466768{col 73}{space 3} .5394239
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2}  .224481{col 32}{space 2}  .077684{col 43}{space 1}    2.89{col 52}{space 3}0.004{col 60}{space 4} .0712547{col 73}{space 3} .3777074
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .1448383{col 32}{space 2} .1452532{col 43}{space 1}    1.00{col 52}{space 3}0.320{col 60}{space 4}-.1420437{col 73}{space 3} .4317203
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 1.230999{col 32}{space 2} .6190125{col 43}{space 1}    1.99{col 52}{space 3}0.048{col 60}{space 4} .0104307{col 73}{space 3} 2.451567
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. mi estimate: svy: reg GHEEur threat1 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest if treatment==1 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       224

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 223.715427
{txt}{col 1}Number of PSUs{col 19}= {res}      224
{txt}{col 49}Average RVI{col 67}= {res}    0.0974
{txt}{col 49}Largest FMI{col 67}= {res}    0.2197
{txt}{col 49}Complete DF{col 67}= {res}       223
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}     93.94
{txt}{col 49}        avg{col 67}= {res}    181.44
{txt}{col 49}        max{col 67}= {res}    214.70
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  15{txt},{res}  217.8{txt}){col 67}= {res}      9.32
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}            GHEEur{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat1 {c |}{col 20}{res}{space 2} .3181346{col 32}{space 2} .0467696{col 43}{space 1}    6.80{col 52}{space 3}0.000{col 60}{space 4} .2259384{col 73}{space 3} .4103307
{txt}{space 12}female {c |}{col 20}{res}{space 2} .0734763{col 32}{space 2} .0850659{col 43}{space 1}    0.86{col 52}{space 3}0.389{col 60}{space 4}-.0942585{col 73}{space 3} .2412112
{txt}{space 15}Age {c |}{col 20}{res}{space 2} .0004878{col 32}{space 2} .0042417{col 43}{space 1}    0.12{col 52}{space 3}0.909{col 60}{space 4}-.0078763{col 73}{space 3}  .008852
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2} -.063857{col 32}{space 2} .0249263{col 43}{space 1}   -2.56{col 52}{space 3}0.011{col 60}{space 4}-.1130454{col 73}{space 3}-.0146686
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2}-.0122543{col 32}{space 2} .1002439{col 43}{space 1}   -0.12{col 52}{space 3}0.903{col 60}{space 4}-.2112925{col 73}{space 3} .1867838
{txt}{space 15}C2  {c |}{col 20}{res}{space 2}-.1964368{col 32}{space 2} .1709982{col 43}{space 1}   -1.15{col 52}{space 3}0.252{col 60}{space 4}-.5336765{col 73}{space 3} .1408029
{txt}{space 15}DE  {c |}{col 20}{res}{space 2} .0224353{col 32}{space 2} .1167773{col 43}{space 1}    0.19{col 52}{space 3}0.848{col 60}{space 4}-.2079781{col 73}{space 3} .2528488
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2} .1167581{col 32}{space 2}  .145817{col 43}{space 1}    0.80{col 52}{space 3}0.425{col 60}{space 4}-.1723403{col 73}{space 3} .4058564
{txt}full time student  {c |}{col 20}{res}{space 2}-.1639866{col 32}{space 2} .2894273{col 43}{space 1}   -0.57{col 52}{space 3}0.572{col 60}{space 4}-.7345526{col 73}{space 3} .4065794
{txt}{space 10}retired  {c |}{col 20}{res}{space 2}-.0082773{col 32}{space 2} .1373017{col 43}{space 1}   -0.06{col 52}{space 3}0.952{col 60}{space 4}-.2791077{col 73}{space 3} .2625531
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2}-.2585321{col 32}{space 2} .1622996{col 43}{space 1}   -1.59{col 52}{space 3}0.113{col 60}{space 4}-.5784368{col 73}{space 3} .0613725
{txt}{space 6}not working  {c |}{col 20}{res}{space 2} .2906183{col 32}{space 2} .1766951{col 43}{space 1}    1.64{col 52}{space 3}0.102{col 60}{space 4}-.0580867{col 73}{space 3} .6393234
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2} .3743147{col 32}{space 2} .1434566{col 43}{space 1}    2.61{col 52}{space 3}0.010{col 60}{space 4} .0912607{col 73}{space 3} .6573687
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2}  .129626{col 32}{space 2} .0739949{col 43}{space 1}    1.75{col 52}{space 3}0.081{col 60}{space 4}-.0162611{col 73}{space 3} .2755131
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .2364284{col 32}{space 2} .1576907{col 43}{space 1}    1.50{col 52}{space 3}0.135{col 60}{space 4}-.0746238{col 73}{space 3} .5474806
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 1.861495{col 32}{space 2} .6083092{col 43}{space 1}    3.06{col 52}{space 3}0.003{col 60}{space 4} .6605861{col 73}{space 3} 3.062403
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHEEur threat2 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest if treatment==1 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       225

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 226.845889
{txt}{col 1}Number of PSUs{col 19}= {res}      225
{txt}{col 49}Average RVI{col 67}= {res}    0.0960
{txt}{col 49}Largest FMI{col 67}= {res}    0.2016
{txt}{col 49}Complete DF{col 67}= {res}       224
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    102.71
{txt}{col 49}        avg{col 67}= {res}    184.50
{txt}{col 49}        max{col 67}= {res}    218.37
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  15{txt},{res}  218.9{txt}){col 67}= {res}      7.12
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}            GHEEur{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat2 {c |}{col 20}{res}{space 2} .2923951{col 32}{space 2} .0462542{col 43}{space 1}    6.32{col 52}{space 3}0.000{col 60}{space 4} .2011701{col 73}{space 3} .3836201
{txt}{space 12}female {c |}{col 20}{res}{space 2} .0011884{col 32}{space 2} .0816838{col 43}{space 1}    0.01{col 52}{space 3}0.988{col 60}{space 4}-.1598709{col 73}{space 3} .1622478
{txt}{space 15}Age {c |}{col 20}{res}{space 2}-.0004957{col 32}{space 2}  .004391{col 43}{space 1}   -0.11{col 52}{space 3}0.910{col 60}{space 4}-.0091548{col 73}{space 3} .0081635
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0586091{col 32}{space 2} .0254979{col 43}{space 1}   -2.30{col 52}{space 3}0.023{col 60}{space 4}-.1089053{col 73}{space 3}-.0083129
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2}-.0214633{col 32}{space 2} .1039376{col 43}{space 1}   -0.21{col 52}{space 3}0.837{col 60}{space 4}-.2276059{col 73}{space 3} .1846793
{txt}{space 15}C2  {c |}{col 20}{res}{space 2}-.2141794{col 32}{space 2} .1470569{col 43}{space 1}   -1.46{col 52}{space 3}0.147{col 60}{space 4}-.5043296{col 73}{space 3} .0759707
{txt}{space 15}DE  {c |}{col 20}{res}{space 2} .0297891{col 32}{space 2} .1270586{col 43}{space 1}    0.23{col 52}{space 3}0.815{col 60}{space 4}-.2208484{col 73}{space 3} .2804266
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2} .0343301{col 32}{space 2} .1445654{col 43}{space 1}    0.24{col 52}{space 3}0.813{col 60}{space 4}-.2523434{col 73}{space 3} .3210036
{txt}full time student  {c |}{col 20}{res}{space 2}-.1151721{col 32}{space 2} .1973076{col 43}{space 1}   -0.58{col 52}{space 3}0.560{col 60}{space 4}-.5043819{col 73}{space 3} .2740378
{txt}{space 10}retired  {c |}{col 20}{res}{space 2} .0416629{col 32}{space 2} .1455266{col 43}{space 1}    0.29{col 52}{space 3}0.775{col 60}{space 4}-.2453816{col 73}{space 3} .3287074
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2}-.2786493{col 32}{space 2} .2037297{col 43}{space 1}   -1.37{col 52}{space 3}0.173{col 60}{space 4}-.6801775{col 73}{space 3} .1228789
{txt}{space 6}not working  {c |}{col 20}{res}{space 2} .3425272{col 32}{space 2} .1931246{col 43}{space 1}    1.77{col 52}{space 3}0.078{col 60}{space 4}-.0384983{col 73}{space 3} .7235527
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2} .5500854{col 32}{space 2} .1979069{col 43}{space 1}    2.78{col 52}{space 3}0.006{col 60}{space 4} .1599308{col 73}{space 3}   .94024
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .1484903{col 32}{space 2} .0760823{col 43}{space 1}    1.95{col 52}{space 3}0.052{col 60}{space 4}   -.0015{col 73}{space 3} .2984805
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .1398744{col 32}{space 2} .1682285{col 43}{space 1}    0.83{col 52}{space 3}0.407{col 60}{space 4}-.1918559{col 73}{space 3} .4716047
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 1.668765{col 32}{space 2} .6695055{col 43}{space 1}    2.49{col 52}{space 3}0.014{col 60}{space 4} .3481755{col 73}{space 3} 2.989354
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHEEur threat3 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest if treatment==1 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       226

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 227.845889
{txt}{col 1}Number of PSUs{col 19}= {res}      226
{txt}{col 49}Average RVI{col 67}= {res}    0.0868
{txt}{col 49}Largest FMI{col 67}= {res}    0.2078
{txt}{col 49}Complete DF{col 67}= {res}       225
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}     99.94
{txt}{col 49}        avg{col 67}= {res}    187.29
{txt}{col 49}        max{col 67}= {res}    219.71
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  15{txt},{res}  220.3{txt}){col 67}= {res}      8.12
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}            GHEEur{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat3 {c |}{col 20}{res}{space 2} .2915911{col 32}{space 2} .0495526{col 43}{space 1}    5.88{col 52}{space 3}0.000{col 60}{space 4} .1939283{col 73}{space 3} .3892539
{txt}{space 12}female {c |}{col 20}{res}{space 2} .0369833{col 32}{space 2} .0824535{col 43}{space 1}    0.45{col 52}{space 3}0.654{col 60}{space 4}-.1255909{col 73}{space 3} .1995576
{txt}{space 15}Age {c |}{col 20}{res}{space 2} .0000147{col 32}{space 2} .0044927{col 43}{space 1}    0.00{col 52}{space 3}0.997{col 60}{space 4} -.008843{col 73}{space 3} .0088723
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0446182{col 32}{space 2} .0262418{col 43}{space 1}   -1.70{col 52}{space 3}0.091{col 60}{space 4}-.0963913{col 73}{space 3}  .007155
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2}  .008494{col 32}{space 2} .1024846{col 43}{space 1}    0.08{col 52}{space 3}0.934{col 60}{space 4}-.1948339{col 73}{space 3} .2118218
{txt}{space 15}C2  {c |}{col 20}{res}{space 2} -.160548{col 32}{space 2}   .16001{col 43}{space 1}   -1.00{col 52}{space 3}0.317{col 60}{space 4}-.4761184{col 73}{space 3} .1550224
{txt}{space 15}DE  {c |}{col 20}{res}{space 2} .0457413{col 32}{space 2} .1256825{col 43}{space 1}    0.36{col 52}{space 3}0.716{col 60}{space 4}-.2021604{col 73}{space 3} .2936431
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2} .0758099{col 32}{space 2} .1472372{col 43}{space 1}    0.51{col 52}{space 3}0.608{col 60}{space 4}-.2159885{col 73}{space 3} .3676083
{txt}full time student  {c |}{col 20}{res}{space 2}-.2212337{col 32}{space 2} .2406872{col 43}{space 1}   -0.92{col 52}{space 3}0.359{col 60}{space 4}-.6957639{col 73}{space 3} .2532965
{txt}{space 10}retired  {c |}{col 20}{res}{space 2} -.011813{col 32}{space 2} .1404287{col 43}{space 1}   -0.08{col 52}{space 3}0.933{col 60}{space 4}-.2887613{col 73}{space 3} .2651353
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2}-.2397643{col 32}{space 2} .2095798{col 43}{space 1}   -1.14{col 52}{space 3}0.254{col 60}{space 4}-.6528083{col 73}{space 3} .1732798
{txt}{space 6}not working  {c |}{col 20}{res}{space 2}  .344176{col 32}{space 2} .1804601{col 43}{space 1}    1.91{col 52}{space 3}0.058{col 60}{space 4}-.0118934{col 73}{space 3} .7002454
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2} .4274723{col 32}{space 2} .1744813{col 43}{space 1}    2.45{col 52}{space 3}0.015{col 60}{space 4} .0833982{col 73}{space 3} .7715463
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .1452467{col 32}{space 2} .0772655{col 43}{space 1}    1.88{col 52}{space 3}0.061{col 60}{space 4}-.0070535{col 73}{space 3} .2975469
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .2991984{col 32}{space 2} .1644007{col 43}{space 1}    1.82{col 52}{space 3}0.070{col 60}{space 4}-.0249843{col 73}{space 3}  .623381
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 1.416738{col 32}{space 2} .6559254{col 43}{space 1}    2.16{col 52}{space 3}0.032{col 60}{space 4} .1221803{col 73}{space 3} 2.711295
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHEEur threat4 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest if treatment==1 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       226

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 227.845889
{txt}{col 1}Number of PSUs{col 19}= {res}      226
{txt}{col 49}Average RVI{col 67}= {res}    0.0847
{txt}{col 49}Largest FMI{col 67}= {res}    0.2248
{txt}{col 49}Complete DF{col 67}= {res}       225
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}     92.12
{txt}{col 49}        avg{col 67}= {res}    188.05
{txt}{col 49}        max{col 67}= {res}    219.85
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  15{txt},{res}  220.5{txt}){col 67}= {res}      7.06
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}            GHEEur{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat4 {c |}{col 20}{res}{space 2} .2285554{col 32}{space 2} .0393564{col 43}{space 1}    5.81{col 52}{space 3}0.000{col 60}{space 4} .1509832{col 73}{space 3} .3061276
{txt}{space 12}female {c |}{col 20}{res}{space 2} .0286988{col 32}{space 2} .0874915{col 43}{space 1}    0.33{col 52}{space 3}0.743{col 60}{space 4}-.1437868{col 73}{space 3} .2011844
{txt}{space 15}Age {c |}{col 20}{res}{space 2}  .001414{col 32}{space 2} .0044022{col 43}{space 1}    0.32{col 52}{space 3}0.748{col 60}{space 4}-.0072654{col 73}{space 3} .0100934
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0522458{col 32}{space 2} .0251472{col 43}{space 1}   -2.08{col 52}{space 3}0.039{col 60}{space 4}-.1018541{col 73}{space 3}-.0026375
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2}-.0141812{col 32}{space 2}  .101338{col 43}{space 1}   -0.14{col 52}{space 3}0.889{col 60}{space 4}-.2153352{col 73}{space 3} .1869728
{txt}{space 15}C2  {c |}{col 20}{res}{space 2} -.180917{col 32}{space 2} .1645118{col 43}{space 1}   -1.10{col 52}{space 3}0.273{col 60}{space 4}-.5053583{col 73}{space 3} .1435243
{txt}{space 15}DE  {c |}{col 20}{res}{space 2} .0314676{col 32}{space 2} .1331309{col 43}{space 1}    0.24{col 52}{space 3}0.813{col 60}{space 4}-.2310627{col 73}{space 3} .2939979
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2} .0289519{col 32}{space 2} .1355164{col 43}{space 1}    0.21{col 52}{space 3}0.831{col 60}{space 4}-.2401906{col 73}{space 3} .2980943
{txt}full time student  {c |}{col 20}{res}{space 2}-.1381287{col 32}{space 2} .2843473{col 43}{space 1}   -0.49{col 52}{space 3}0.628{col 60}{space 4}-.6986995{col 73}{space 3}  .422442
{txt}{space 10}retired  {c |}{col 20}{res}{space 2}-.0702591{col 32}{space 2} .1387998{col 43}{space 1}   -0.51{col 52}{space 3}0.613{col 60}{space 4}-.3439972{col 73}{space 3} .2034789
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2}-.1739793{col 32}{space 2} .2014651{col 43}{space 1}   -0.86{col 52}{space 3}0.389{col 60}{space 4}-.5710295{col 73}{space 3} .2230708
{txt}{space 6}not working  {c |}{col 20}{res}{space 2} .3785823{col 32}{space 2} .1992985{col 43}{space 1}    1.90{col 52}{space 3}0.059{col 60}{space 4}-.0145077{col 73}{space 3} .7716722
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2} .5580378{col 32}{space 2} .1631587{col 43}{space 1}    3.42{col 52}{space 3}0.001{col 60}{space 4} .2362683{col 73}{space 3} .8798074
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .1831929{col 32}{space 2} .0717473{col 43}{space 1}    2.55{col 52}{space 3}0.011{col 60}{space 4} .0417653{col 73}{space 3} .3246206
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .2009742{col 32}{space 2} .1661507{col 43}{space 1}    1.21{col 52}{space 3}0.228{col 60}{space 4} -.126628{col 73}{space 3} .5285765
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 1.409923{col 32}{space 2} .6431672{col 43}{space 1}    2.19{col 52}{space 3}0.030{col 60}{space 4} .1409477{col 73}{space 3} 2.678899
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHEEur threat5 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest if treatment==1 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       226

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 227.845889
{txt}{col 1}Number of PSUs{col 19}= {res}      226
{txt}{col 49}Average RVI{col 67}= {res}    0.0981
{txt}{col 49}Largest FMI{col 67}= {res}    0.2460
{txt}{col 49}Complete DF{col 67}= {res}       225
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}     83.38
{txt}{col 49}        avg{col 67}= {res}    183.04
{txt}{col 49}        max{col 67}= {res}    220.13
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  15{txt},{res}  219.8{txt}){col 67}= {res}     10.17
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}            GHEEur{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat5 {c |}{col 20}{res}{space 2} .3124582{col 32}{space 2} .0428829{col 43}{space 1}    7.29{col 52}{space 3}0.000{col 60}{space 4} .2279275{col 73}{space 3}  .396989
{txt}{space 12}female {c |}{col 20}{res}{space 2}-.0318992{col 32}{space 2} .0801132{col 43}{space 1}   -0.40{col 52}{space 3}0.691{col 60}{space 4}-.1898646{col 73}{space 3} .1260663
{txt}{space 15}Age {c |}{col 20}{res}{space 2} .0017907{col 32}{space 2} .0041038{col 43}{space 1}    0.44{col 52}{space 3}0.663{col 60}{space 4}-.0063027{col 73}{space 3} .0098841
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0457574{col 32}{space 2} .0232976{col 43}{space 1}   -1.96{col 52}{space 3}0.051{col 60}{space 4}-.0917242{col 73}{space 3} .0002095
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2} -.006288{col 32}{space 2} .0974967{col 43}{space 1}   -0.06{col 52}{space 3}0.949{col 60}{space 4}-.1999555{col 73}{space 3} .1873795
{txt}{space 15}C2  {c |}{col 20}{res}{space 2}-.2132132{col 32}{space 2} .1673845{col 43}{space 1}   -1.27{col 52}{space 3}0.204{col 60}{space 4}-.5433157{col 73}{space 3} .1168893
{txt}{space 15}DE  {c |}{col 20}{res}{space 2} .0506395{col 32}{space 2} .1196392{col 43}{space 1}    0.42{col 52}{space 3}0.673{col 60}{space 4}-.1853665{col 73}{space 3} .2866455
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2} .0520702{col 32}{space 2} .1305289{col 43}{space 1}    0.40{col 52}{space 3}0.691{col 60}{space 4}-.2075289{col 73}{space 3} .3116694
{txt}full time student  {c |}{col 20}{res}{space 2}-.1298376{col 32}{space 2} .2734558{col 43}{space 1}   -0.47{col 52}{space 3}0.635{col 60}{space 4}-.6689322{col 73}{space 3} .4092571
{txt}{space 10}retired  {c |}{col 20}{res}{space 2}-.0838693{col 32}{space 2} .1274812{col 43}{space 1}   -0.66{col 52}{space 3}0.511{col 60}{space 4}-.3353516{col 73}{space 3} .1676129
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2}-.1957703{col 32}{space 2} .2137935{col 43}{space 1}   -0.92{col 52}{space 3}0.361{col 60}{space 4}-.6171143{col 73}{space 3} .2255737
{txt}{space 6}not working  {c |}{col 20}{res}{space 2} .3299543{col 32}{space 2} .1825603{col 43}{space 1}    1.81{col 52}{space 3}0.072{col 60}{space 4}-.0302653{col 73}{space 3} .6901739
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2} .4951963{col 32}{space 2} .1946723{col 43}{space 1}    2.54{col 52}{space 3}0.012{col 60}{space 4} .1114022{col 73}{space 3} .8789903
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .1188337{col 32}{space 2} .0725857{col 43}{space 1}    1.64{col 52}{space 3}0.103{col 60}{space 4}-.0243195{col 73}{space 3} .2619869
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .2047957{col 32}{space 2} .1556745{col 43}{space 1}    1.32{col 52}{space 3}0.190{col 60}{space 4} -.102152{col 73}{space 3} .5117435
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 1.332495{col 32}{space 2} .5868583{col 43}{space 1}    2.27{col 52}{space 3}0.024{col 60}{space 4} .1742738{col 73}{space 3} 2.490715
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. mi estimate: svy: reg GHwhite threat1 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest if treatment==1 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       226

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 222.826495
{txt}{col 1}Number of PSUs{col 19}= {res}      226
{txt}{col 49}Average RVI{col 67}= {res}    0.1598
{txt}{col 49}Largest FMI{col 67}= {res}    0.2903
{txt}{col 49}Complete DF{col 67}= {res}       225
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}     68.16
{txt}{col 49}        avg{col 67}= {res}    149.50
{txt}{col 49}        max{col 67}= {res}    211.72
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  15{txt},{res}  215.0{txt}){col 67}= {res}      1.31
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.1987

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           GHwhite{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat1 {c |}{col 20}{res}{space 2}-.0288181{col 32}{space 2} .0789634{col 43}{space 1}   -0.36{col 52}{space 3}0.716{col 60}{space 4}-.1850076{col 73}{space 3} .1273714
{txt}{space 12}female {c |}{col 20}{res}{space 2} .0226512{col 32}{space 2} .1714083{col 43}{space 1}    0.13{col 52}{space 3}0.895{col 60}{space 4}-.3154038{col 73}{space 3} .3607062
{txt}{space 15}Age {c |}{col 20}{res}{space 2}-.0170828{col 32}{space 2} .0086981{col 43}{space 1}   -1.96{col 52}{space 3}0.051{col 60}{space 4}-.0342606{col 73}{space 3} .0000951
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}  .008239{col 32}{space 2} .0541815{col 43}{space 1}    0.15{col 52}{space 3}0.879{col 60}{space 4}-.0988397{col 73}{space 3} .1153176
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2} .0437339{col 32}{space 2} .2229001{col 43}{space 1}    0.20{col 52}{space 3}0.845{col 60}{space 4}-.3966823{col 73}{space 3} .4841501
{txt}{space 15}C2  {c |}{col 20}{res}{space 2}-.2697051{col 32}{space 2} .2407809{col 43}{space 1}   -1.12{col 52}{space 3}0.264{col 60}{space 4}-.7443401{col 73}{space 3} .2049299
{txt}{space 15}DE  {c |}{col 20}{res}{space 2}-.3057752{col 32}{space 2} .2334378{col 43}{space 1}   -1.31{col 52}{space 3}0.192{col 60}{space 4}-.7665678{col 73}{space 3} .1550174
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2} .3560316{col 32}{space 2} .2885194{col 43}{space 1}    1.23{col 52}{space 3}0.219{col 60}{space 4}-.2129153{col 73}{space 3} .9249786
{txt}full time student  {c |}{col 20}{res}{space 2}-1.100353{col 32}{space 2} .3267662{col 43}{space 1}   -3.37{col 52}{space 3}0.001{col 60}{space 4}-1.746927{col 73}{space 3} -.453779
{txt}{space 10}retired  {c |}{col 20}{res}{space 2} .2182676{col 32}{space 2}  .246748{col 43}{space 1}    0.88{col 52}{space 3}0.379{col 60}{space 4}-.2714294{col 73}{space 3} .7079645
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2} .0546728{col 32}{space 2} .5002527{col 43}{space 1}    0.11{col 52}{space 3}0.913{col 60}{space 4} -.932495{col 73}{space 3} 1.041841
{txt}{space 6}not working  {c |}{col 20}{res}{space 2} .0342714{col 32}{space 2} .3625868{col 43}{space 1}    0.09{col 52}{space 3}0.925{col 60}{space 4} -.680634{col 73}{space 3} .7491768
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2} .4310805{col 32}{space 2} .3298638{col 43}{space 1}    1.31{col 52}{space 3}0.194{col 60}{space 4}-.2234162{col 73}{space 3} 1.085577
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .0471605{col 32}{space 2} .1554976{col 43}{space 1}    0.30{col 52}{space 3}0.763{col 60}{space 4}-.2631174{col 73}{space 3} .3574383
{txt}{space 11}selfest {c |}{col 20}{res}{space 2}   .44456{col 32}{space 2} .3427386{col 43}{space 1}    1.30{col 52}{space 3}0.197{col 60}{space 4}-.2330799{col 73}{space 3}   1.1222
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 2.377717{col 32}{space 2} 1.339145{col 43}{space 1}    1.78{col 52}{space 3}0.079{col 60}{space 4}-.2757129{col 73}{space 3} 5.031147
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHwhite threat2 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest if treatment==1 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       222

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 218.878651
{txt}{col 1}Number of PSUs{col 19}= {res}      222
{txt}{col 49}Average RVI{col 67}= {res}    0.1554
{txt}{col 49}Largest FMI{col 67}= {res}    0.3110
{txt}{col 49}Complete DF{col 67}= {res}       221
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}     61.81
{txt}{col 49}        avg{col 67}= {res}    149.90
{txt}{col 49}        max{col 67}= {res}    205.99
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  15{txt},{res}  211.6{txt}){col 67}= {res}      0.92
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.5419

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           GHwhite{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat2 {c |}{col 20}{res}{space 2}-.0321259{col 32}{space 2} .0877571{col 43}{space 1}   -0.37{col 52}{space 3}0.715{col 60}{space 4}-.2054448{col 73}{space 3}  .141193
{txt}{space 12}female {c |}{col 20}{res}{space 2} .0412552{col 32}{space 2} .1716861{col 43}{space 1}    0.24{col 52}{space 3}0.810{col 60}{space 4}-.2974667{col 73}{space 3} .3799771
{txt}{space 15}Age {c |}{col 20}{res}{space 2} -.015902{col 32}{space 2} .0086127{col 43}{space 1}   -1.85{col 52}{space 3}0.067{col 60}{space 4}-.0329133{col 73}{space 3} .0011092
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0109793{col 32}{space 2} .0549266{col 43}{space 1}   -0.20{col 52}{space 3}0.842{col 60}{space 4}-.1195186{col 73}{space 3}   .09756
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2} -.059324{col 32}{space 2} .2299482{col 43}{space 1}   -0.26{col 52}{space 3}0.797{col 60}{space 4}-.5137986{col 73}{space 3} .3951505
{txt}{space 15}C2  {c |}{col 20}{res}{space 2}-.2994549{col 32}{space 2}  .256158{col 43}{space 1}   -1.17{col 52}{space 3}0.244{col 60}{space 4}-.8044825{col 73}{space 3} .2055726
{txt}{space 15}DE  {c |}{col 20}{res}{space 2}-.3245319{col 32}{space 2} .2329057{col 43}{space 1}   -1.39{col 52}{space 3}0.166{col 60}{space 4} -.784678{col 73}{space 3} .1356143
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2}  .404056{col 32}{space 2} .2980523{col 43}{space 1}    1.36{col 52}{space 3}0.177{col 60}{space 4} -.183698{col 73}{space 3} .9918099
{txt}full time student  {c |}{col 20}{res}{space 2}-.5523859{col 32}{space 2} .4957005{col 43}{space 1}   -1.11{col 52}{space 3}0.267{col 60}{space 4}-1.530128{col 73}{space 3} .4253564
{txt}{space 10}retired  {c |}{col 20}{res}{space 2} .1916883{col 32}{space 2}  .246677{col 43}{space 1}    0.78{col 52}{space 3}0.439{col 60}{space 4}-.2985544{col 73}{space 3}  .681931
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2}-.1604508{col 32}{space 2} .4728362{col 43}{space 1}   -0.34{col 52}{space 3}0.735{col 60}{space 4}-1.094526{col 73}{space 3} .7736242
{txt}{space 6}not working  {c |}{col 20}{res}{space 2} .0503472{col 32}{space 2} .3626202{col 43}{space 1}    0.14{col 52}{space 3}0.890{col 60}{space 4}-.6647049{col 73}{space 3} .7653994
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2} .4662665{col 32}{space 2} .3219242{col 43}{space 1}    1.45{col 52}{space 3}0.151{col 60}{space 4}-.1731714{col 73}{space 3} 1.105704
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .0934099{col 32}{space 2} .1621625{col 43}{space 1}    0.58{col 52}{space 3}0.567{col 60}{space 4}-.2307686{col 73}{space 3} .4175885
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .4450376{col 32}{space 2} .3566025{col 43}{space 1}    1.25{col 52}{space 3}0.214{col 60}{space 4}-.2595902{col 73}{space 3} 1.149666
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 2.537419{col 32}{space 2}  1.34266{col 43}{space 1}    1.89{col 52}{space 3}0.061{col 60}{space 4}-.1230887{col 73}{space 3} 5.197927
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHwhite threat3 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest if treatment==1 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       226

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 223.507878
{txt}{col 1}Number of PSUs{col 19}= {res}      226
{txt}{col 49}Average RVI{col 67}= {res}    0.1523
{txt}{col 49}Largest FMI{col 67}= {res}    0.3083
{txt}{col 49}Complete DF{col 67}= {res}       225
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}     62.99
{txt}{col 49}        avg{col 67}= {res}    152.21
{txt}{col 49}        max{col 67}= {res}    211.48
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  15{txt},{res}  215.7{txt}){col 67}= {res}      1.25
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.2345

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           GHwhite{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat3 {c |}{col 20}{res}{space 2}-.0074927{col 32}{space 2} .0781278{col 43}{space 1}   -0.10{col 52}{space 3}0.924{col 60}{space 4}-.1617066{col 73}{space 3} .1467212
{txt}{space 12}female {c |}{col 20}{res}{space 2} .0201923{col 32}{space 2} .1706618{col 43}{space 1}    0.12{col 52}{space 3}0.906{col 60}{space 4}-.3164291{col 73}{space 3} .3568137
{txt}{space 15}Age {c |}{col 20}{res}{space 2}-.0167786{col 32}{space 2} .0087685{col 43}{space 1}   -1.91{col 52}{space 3}0.057{col 60}{space 4}-.0340927{col 73}{space 3} .0005355
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2} .0107275{col 32}{space 2} .0546296{col 43}{space 1}    0.20{col 52}{space 3}0.845{col 60}{space 4}-.0972444{col 73}{space 3} .1186994
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2} .0318566{col 32}{space 2} .2220351{col 43}{space 1}    0.14{col 52}{space 3}0.886{col 60}{space 4}-.4068347{col 73}{space 3} .4705479
{txt}{space 15}C2  {c |}{col 20}{res}{space 2}-.2658681{col 32}{space 2} .2416052{col 43}{space 1}   -1.10{col 52}{space 3}0.272{col 60}{space 4}-.7421311{col 73}{space 3} .2103949
{txt}{space 15}DE  {c |}{col 20}{res}{space 2}-.3085071{col 32}{space 2}  .232414{col 43}{space 1}   -1.33{col 52}{space 3}0.186{col 60}{space 4}-.7673076{col 73}{space 3} .1502934
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2} .3631144{col 32}{space 2} .2885996{col 43}{space 1}    1.26{col 52}{space 3}0.210{col 60}{space 4} -.205982{col 73}{space 3} .9322108
{txt}full time student  {c |}{col 20}{res}{space 2}-1.081305{col 32}{space 2} .3320976{col 43}{space 1}   -3.26{col 52}{space 3}0.001{col 60}{space 4}-1.738259{col 73}{space 3} -.424352
{txt}{space 10}retired  {c |}{col 20}{res}{space 2} .2176708{col 32}{space 2} .2475209{col 43}{space 1}    0.88{col 52}{space 3}0.381{col 60}{space 4}-.2734542{col 73}{space 3} .7087957
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2}  .072514{col 32}{space 2} .5019172{col 43}{space 1}    0.14{col 52}{space 3}0.885{col 60}{space 4} -.917919{col 73}{space 3} 1.062947
{txt}{space 6}not working  {c |}{col 20}{res}{space 2} .0408948{col 32}{space 2} .3637265{col 43}{space 1}    0.11{col 52}{space 3}0.911{col 60}{space 4}-.6762671{col 73}{space 3} .7580567
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2} .4271113{col 32}{space 2} .3406394{col 43}{space 1}    1.25{col 52}{space 3}0.213{col 60}{space 4}-.2480716{col 73}{space 3} 1.102294
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .0432105{col 32}{space 2} .1553418{col 43}{space 1}    0.28{col 52}{space 3}0.782{col 60}{space 4} -.267216{col 73}{space 3}  .353637
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .4048257{col 32}{space 2} .3401465{col 43}{space 1}    1.19{col 52}{space 3}0.236{col 60}{space 4}-.2676815{col 73}{space 3} 1.077333
{txt}{space 13}_cons {c |}{col 20}{res}{space 2}   2.2962{col 32}{space 2} 1.359733{col 43}{space 1}    1.69{col 52}{space 3}0.094{col 60}{space 4}-.3989668{col 73}{space 3} 4.991367
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHwhite threat4 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest if treatment==1 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       224

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 221.071247
{txt}{col 1}Number of PSUs{col 19}= {res}      224
{txt}{col 49}Average RVI{col 67}= {res}    0.1675
{txt}{col 49}Largest FMI{col 67}= {res}    0.2955
{txt}{col 49}Complete DF{col 67}= {res}       223
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}     66.37
{txt}{col 49}        avg{col 67}= {res}    148.16
{txt}{col 49}        max{col 67}= {res}    209.22
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  15{txt},{res}  212.5{txt}){col 67}= {res}      1.28
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.2153

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           GHwhite{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat4 {c |}{col 20}{res}{space 2}-.0801505{col 32}{space 2} .0764378{col 43}{space 1}   -1.05{col 52}{space 3}0.296{col 60}{space 4}-.2312951{col 73}{space 3} .0709941
{txt}{space 12}female {c |}{col 20}{res}{space 2} .0179235{col 32}{space 2} .1717703{col 43}{space 1}    0.10{col 52}{space 3}0.917{col 60}{space 4}-.3208984{col 73}{space 3} .3567454
{txt}{space 15}Age {c |}{col 20}{res}{space 2}-.0168952{col 32}{space 2} .0086797{col 43}{space 1}   -1.95{col 52}{space 3}0.053{col 60}{space 4}-.0340388{col 73}{space 3} .0002483
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2} .0055241{col 32}{space 2} .0549672{col 43}{space 1}    0.10{col 52}{space 3}0.920{col 60}{space 4}-.1030851{col 73}{space 3} .1141332
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2} .0406635{col 32}{space 2} .2258971{col 43}{space 1}    0.18{col 52}{space 3}0.857{col 60}{space 4}-.4056877{col 73}{space 3} .4870147
{txt}{space 15}C2  {c |}{col 20}{res}{space 2}-.2571143{col 32}{space 2} .2461686{col 43}{space 1}   -1.04{col 52}{space 3}0.297{col 60}{space 4} -.742403{col 73}{space 3} .2281744
{txt}{space 15}DE  {c |}{col 20}{res}{space 2}-.2948291{col 32}{space 2} .2319096{col 43}{space 1}   -1.27{col 52}{space 3}0.205{col 60}{space 4}-.7527361{col 73}{space 3} .1630779
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2} .3946986{col 32}{space 2} .3008995{col 43}{space 1}    1.31{col 52}{space 3}0.191{col 60}{space 4}-.1986377{col 73}{space 3} .9880349
{txt}full time student  {c |}{col 20}{res}{space 2}-1.064792{col 32}{space 2} .3241513{col 43}{space 1}   -3.28{col 52}{space 3}0.001{col 60}{space 4}-1.706209{col 73}{space 3}-.4233748
{txt}{space 10}retired  {c |}{col 20}{res}{space 2} .2476239{col 32}{space 2} .2487471{col 43}{space 1}    1.00{col 52}{space 3}0.322{col 60}{space 4}-.2457795{col 73}{space 3} .7410273
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2} .0428064{col 32}{space 2} .5014478{col 43}{space 1}    0.09{col 52}{space 3}0.932{col 60}{space 4}-.9468622{col 73}{space 3} 1.032475
{txt}{space 6}not working  {c |}{col 20}{res}{space 2} .0437922{col 32}{space 2} .3639197{col 43}{space 1}    0.12{col 52}{space 3}0.904{col 60}{space 4}-.6737924{col 73}{space 3} .7613769
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2}  .381213{col 32}{space 2} .3198048{col 43}{space 1}    1.19{col 52}{space 3}0.236{col 60}{space 4}-.2537753{col 73}{space 3} 1.016201
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .0689151{col 32}{space 2} .1590053{col 43}{space 1}    0.43{col 52}{space 3}0.666{col 60}{space 4}-.2485158{col 73}{space 3}  .386346
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .4646067{col 32}{space 2} .3398589{col 43}{space 1}    1.37{col 52}{space 3}0.174{col 60}{space 4}-.2077336{col 73}{space 3} 1.136947
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 2.555899{col 32}{space 2} 1.375157{col 43}{space 1}    1.86{col 52}{space 3}0.066{col 60}{space 4}-.1679765{col 73}{space 3} 5.279774
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHwhite threat5 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest if treatment==1 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       224

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 221.752629
{txt}{col 1}Number of PSUs{col 19}= {res}      224
{txt}{col 49}Average RVI{col 67}= {res}    0.1620
{txt}{col 49}Largest FMI{col 67}= {res}    0.3158
{txt}{col 49}Complete DF{col 67}= {res}       223
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}     60.76
{txt}{col 49}        avg{col 67}= {res}    151.39
{txt}{col 49}        max{col 67}= {res}    207.45
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  15{txt},{res}  213.0{txt}){col 67}= {res}      1.26
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.2331

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           GHwhite{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat5 {c |}{col 20}{res}{space 2}-.0133112{col 32}{space 2} .0800123{col 43}{space 1}   -0.17{col 52}{space 3}0.868{col 60}{space 4}-.1711986{col 73}{space 3} .1445761
{txt}{space 12}female {c |}{col 20}{res}{space 2} .0613296{col 32}{space 2} .1708869{col 43}{space 1}    0.36{col 52}{space 3}0.720{col 60}{space 4}-.2757826{col 73}{space 3} .3984418
{txt}{space 15}Age {c |}{col 20}{res}{space 2}-.0161074{col 32}{space 2} .0087015{col 43}{space 1}   -1.85{col 52}{space 3}0.066{col 60}{space 4}-.0332919{col 73}{space 3} .0010772
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2} .0052193{col 32}{space 2} .0542134{col 43}{space 1}    0.10{col 52}{space 3}0.923{col 60}{space 4}-.1018684{col 73}{space 3} .1123069
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2}-.0248773{col 32}{space 2} .2221593{col 43}{space 1}   -0.11{col 52}{space 3}0.911{col 60}{space 4}-.4638914{col 73}{space 3} .4141368
{txt}{space 15}C2  {c |}{col 20}{res}{space 2}-.2917965{col 32}{space 2} .2413114{col 43}{space 1}   -1.21{col 52}{space 3}0.228{col 60}{space 4}-.7675335{col 73}{space 3} .1839405
{txt}{space 15}DE  {c |}{col 20}{res}{space 2} -.327343{col 32}{space 2} .2335472{col 43}{space 1}   -1.40{col 52}{space 3}0.163{col 60}{space 4}-.7884017{col 73}{space 3} .1337157
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2} .4028417{col 32}{space 2} .2970995{col 43}{space 1}    1.36{col 52}{space 3}0.177{col 60}{space 4}-.1830101{col 73}{space 3} .9886935
{txt}full time student  {c |}{col 20}{res}{space 2}-1.044179{col 32}{space 2} .3208712{col 43}{space 1}   -3.25{col 52}{space 3}0.001{col 60}{space 4}-1.679127{col 73}{space 3}-.4092318
{txt}{space 10}retired  {c |}{col 20}{res}{space 2} .2357659{col 32}{space 2} .2456133{col 43}{space 1}    0.96{col 52}{space 3}0.339{col 60}{space 4}-.2514202{col 73}{space 3}  .722952
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2}  .085798{col 32}{space 2} .5049128{col 43}{space 1}    0.17{col 52}{space 3}0.865{col 60}{space 4}-.9105637{col 73}{space 3}  1.08216
{txt}{space 6}not working  {c |}{col 20}{res}{space 2} .0449459{col 32}{space 2} .3644563{col 43}{space 1}    0.12{col 52}{space 3}0.902{col 60}{space 4}-.6736615{col 73}{space 3} .7635532
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2} .4249892{col 32}{space 2} .3199184{col 43}{space 1}    1.33{col 52}{space 3}0.187{col 60}{space 4}-.2103716{col 73}{space 3}  1.06035
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .0316339{col 32}{space 2} .1590292{col 43}{space 1}    0.20{col 52}{space 3}0.843{col 60}{space 4}-.2863898{col 73}{space 3} .3496576
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .4889691{col 32}{space 2} .3393883{col 43}{space 1}    1.44{col 52}{space 3}0.152{col 60}{space 4}-.1823225{col 73}{space 3} 1.160261
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 2.357204{col 32}{space 2} 1.349582{col 43}{space 1}    1.75{col 52}{space 3}0.083{col 60}{space 4} -.314888{col 73}{space 3} 5.029295
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. * decoupled
. mi estimate: svy: reg GHblack threat1 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest if treatment==0 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       416

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 417.914422
{txt}{col 1}Number of PSUs{col 19}= {res}      416
{txt}{col 49}Average RVI{col 67}= {res}    0.1218
{txt}{col 49}Largest FMI{col 67}= {res}    0.2745
{txt}{col 49}Complete DF{col 67}= {res}       415
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}     91.47
{txt}{col 49}        avg{col 67}= {res}    255.79
{txt}{col 49}        max{col 67}= {res}    390.14
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  15{txt},{res}  398.3{txt}){col 67}= {res}      8.77
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           GHblack{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat1 {c |}{col 20}{res}{space 2} .1272692{col 32}{space 2} .0376629{col 43}{space 1}    3.38{col 52}{space 3}0.001{col 60}{space 4} .0531764{col 73}{space 3} .2013621
{txt}{space 12}female {c |}{col 20}{res}{space 2}-.1139002{col 32}{space 2} .0555818{col 43}{space 1}   -2.05{col 52}{space 3}0.041{col 60}{space 4}-.2232629{col 73}{space 3}-.0045375
{txt}{space 15}Age {c |}{col 20}{res}{space 2}-.0028072{col 32}{space 2} .0032826{col 43}{space 1}   -0.86{col 52}{space 3}0.394{col 60}{space 4}-.0092843{col 73}{space 3}   .00367
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2} -.020413{col 32}{space 2} .0187236{col 43}{space 1}   -1.09{col 52}{space 3}0.278{col 60}{space 4}-.0576026{col 73}{space 3} .0167766
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2} .0369777{col 32}{space 2}  .069944{col 43}{space 1}    0.53{col 52}{space 3}0.597{col 60}{space 4}-.1007173{col 73}{space 3} .1746727
{txt}{space 15}C2  {c |}{col 20}{res}{space 2}-.0169801{col 32}{space 2} .0945951{col 43}{space 1}   -0.18{col 52}{space 3}0.858{col 60}{space 4} -.202982{col 73}{space 3} .1690218
{txt}{space 15}DE  {c |}{col 20}{res}{space 2}-.0392542{col 32}{space 2} .0914596{col 43}{space 1}   -0.43{col 52}{space 3}0.668{col 60}{space 4}-.2197184{col 73}{space 3}   .14121
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2}-.1112659{col 32}{space 2} .0854828{col 43}{space 1}   -1.30{col 52}{space 3}0.194{col 60}{space 4}-.2794144{col 73}{space 3} .0568827
{txt}full time student  {c |}{col 20}{res}{space 2} -.162074{col 32}{space 2} .1441037{col 43}{space 1}   -1.12{col 52}{space 3}0.262{col 60}{space 4}-.4456064{col 73}{space 3} .1214584
{txt}{space 10}retired  {c |}{col 20}{res}{space 2}  .138021{col 32}{space 2} .0970252{col 43}{space 1}    1.42{col 52}{space 3}0.156{col 60}{space 4}-.0529472{col 73}{space 3} .3289893
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2}  .179019{col 32}{space 2} .2066052{col 43}{space 1}    0.87{col 52}{space 3}0.387{col 60}{space 4}-.2274589{col 73}{space 3}  .585497
{txt}{space 6}not working  {c |}{col 20}{res}{space 2}-.0059965{col 32}{space 2} .1312987{col 43}{space 1}   -0.05{col 52}{space 3}0.964{col 60}{space 4}  -.26518{col 73}{space 3} .2531869
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2} -.196752{col 32}{space 2} .3424842{col 43}{space 1}   -0.57{col 52}{space 3}0.566{col 60}{space 4}-.8700975{col 73}{space 3} .4765934
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .3207769{col 32}{space 2} .0525044{col 43}{space 1}    6.11{col 52}{space 3}0.000{col 60}{space 4} .2171987{col 73}{space 3}  .424355
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .2639567{col 32}{space 2} .1240132{col 43}{space 1}    2.13{col 52}{space 3}0.035{col 60}{space 4} .0191659{col 73}{space 3} .5087474
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 1.754071{col 32}{space 2} .5819489{col 43}{space 1}    3.01{col 52}{space 3}0.003{col 60}{space 4} .6055551{col 73}{space 3} 2.902586
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHblack threat2 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest if treatment==0 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       418

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 419.914422
{txt}{col 1}Number of PSUs{col 19}= {res}      418
{txt}{col 49}Average RVI{col 67}= {res}    0.1173
{txt}{col 49}Largest FMI{col 67}= {res}    0.2511
{txt}{col 49}Complete DF{col 67}= {res}       417
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    104.20
{txt}{col 49}        avg{col 67}= {res}    253.69
{txt}{col 49}        max{col 67}= {res}    394.37
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  15{txt},{res}  400.4{txt}){col 67}= {res}      7.93
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           GHblack{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat2 {c |}{col 20}{res}{space 2} .0555453{col 32}{space 2} .0440108{col 43}{space 1}    1.26{col 52}{space 3}0.208{col 60}{space 4}-.0311325{col 73}{space 3} .1422231
{txt}{space 12}female {c |}{col 20}{res}{space 2}-.0834021{col 32}{space 2} .0553331{col 43}{space 1}   -1.51{col 52}{space 3}0.133{col 60}{space 4}-.1922858{col 73}{space 3} .0254816
{txt}{space 15}Age {c |}{col 20}{res}{space 2}-.0026251{col 32}{space 2} .0033225{col 43}{space 1}   -0.79{col 52}{space 3}0.430{col 60}{space 4}-.0091774{col 73}{space 3} .0039272
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0266536{col 32}{space 2} .0190358{col 43}{space 1}   -1.40{col 52}{space 3}0.164{col 60}{space 4}-.0644014{col 73}{space 3} .0110942
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2} .0266436{col 32}{space 2}   .06892{col 43}{space 1}    0.39{col 52}{space 3}0.699{col 60}{space 4}-.1090186{col 73}{space 3} .1623059
{txt}{space 15}C2  {c |}{col 20}{res}{space 2}-.0123909{col 32}{space 2} .0975944{col 43}{space 1}   -0.13{col 52}{space 3}0.899{col 60}{space 4}-.2042893{col 73}{space 3} .1795075
{txt}{space 15}DE  {c |}{col 20}{res}{space 2}-.0307867{col 32}{space 2} .0883389{col 43}{space 1}   -0.35{col 52}{space 3}0.728{col 60}{space 4}-.2051447{col 73}{space 3} .1435713
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2}-.1417339{col 32}{space 2} .0852432{col 43}{space 1}   -1.66{col 52}{space 3}0.097{col 60}{space 4}-.3093958{col 73}{space 3}  .025928
{txt}full time student  {c |}{col 20}{res}{space 2}-.1838366{col 32}{space 2}  .157436{col 43}{space 1}   -1.17{col 52}{space 3}0.244{col 60}{space 4}  -.49354{col 73}{space 3} .1258667
{txt}{space 10}retired  {c |}{col 20}{res}{space 2} .1219455{col 32}{space 2} .0985004{col 43}{space 1}    1.24{col 52}{space 3}0.217{col 60}{space 4}-.0718835{col 73}{space 3} .3157744
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2} .1214326{col 32}{space 2} .2090785{col 43}{space 1}    0.58{col 52}{space 3}0.562{col 60}{space 4}-.2898693{col 73}{space 3} .5327346
{txt}{space 6}not working  {c |}{col 20}{res}{space 2}-.0214993{col 32}{space 2} .1312604{col 43}{space 1}   -0.16{col 52}{space 3}0.870{col 60}{space 4}-.2806364{col 73}{space 3} .2376379
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2}-.2273774{col 32}{space 2} .3528907{col 43}{space 1}   -0.64{col 52}{space 3}0.520{col 60}{space 4}-.9211596{col 73}{space 3} .4664048
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2}  .354283{col 32}{space 2} .0510415{col 43}{space 1}    6.94{col 52}{space 3}0.000{col 60}{space 4} .2535153{col 73}{space 3} .4550507
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .2869702{col 32}{space 2} .1173026{col 43}{space 1}    2.45{col 52}{space 3}0.016{col 60}{space 4}  .055112{col 73}{space 3} .5188284
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 1.949947{col 32}{space 2} .6006466{col 43}{space 1}    3.25{col 52}{space 3}0.001{col 60}{space 4} .7651435{col 73}{space 3}  3.13475
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHblack threat3 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest if treatment==0 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       418

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 419.914422
{txt}{col 1}Number of PSUs{col 19}= {res}      418
{txt}{col 49}Average RVI{col 67}= {res}    0.1187
{txt}{col 49}Largest FMI{col 67}= {res}    0.2658
{txt}{col 49}Complete DF{col 67}= {res}       417
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}     96.05
{txt}{col 49}        avg{col 67}= {res}    259.89
{txt}{col 49}        max{col 67}= {res}    399.61
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  15{txt},{res}  400.6{txt}){col 67}= {res}      8.58
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           GHblack{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat3 {c |}{col 20}{res}{space 2} .1067242{col 32}{space 2}  .039263{col 43}{space 1}    2.72{col 52}{space 3}0.007{col 60}{space 4} .0294858{col 73}{space 3} .1839626
{txt}{space 12}female {c |}{col 20}{res}{space 2}-.1164139{col 32}{space 2} .0565656{col 43}{space 1}   -2.06{col 52}{space 3}0.040{col 60}{space 4}-.2277083{col 73}{space 3}-.0051195
{txt}{space 15}Age {c |}{col 20}{res}{space 2}-.0030667{col 32}{space 2} .0032329{col 43}{space 1}   -0.95{col 52}{space 3}0.344{col 60}{space 4}-.0094456{col 73}{space 3} .0033122
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0203889{col 32}{space 2} .0190623{col 43}{space 1}   -1.07{col 52}{space 3}0.287{col 60}{space 4} -.058227{col 73}{space 3} .0174491
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2} .0468363{col 32}{space 2} .0702328{col 43}{space 1}    0.67{col 52}{space 3}0.505{col 60}{space 4}-.0914191{col 73}{space 3} .1850917
{txt}{space 15}C2  {c |}{col 20}{res}{space 2} -.011814{col 32}{space 2} .0949305{col 43}{space 1}   -0.12{col 52}{space 3}0.901{col 60}{space 4}-.1984688{col 73}{space 3} .1748408
{txt}{space 15}DE  {c |}{col 20}{res}{space 2}-.0294811{col 32}{space 2} .0916233{col 43}{space 1}   -0.32{col 52}{space 3}0.748{col 60}{space 4}-.2103555{col 73}{space 3} .1513933
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2}-.1144657{col 32}{space 2} .0882888{col 43}{space 1}   -1.30{col 52}{space 3}0.196{col 60}{space 4}-.2881139{col 73}{space 3} .0591826
{txt}full time student  {c |}{col 20}{res}{space 2}-.1805541{col 32}{space 2} .1460978{col 43}{space 1}   -1.24{col 52}{space 3}0.217{col 60}{space 4}-.4680087{col 73}{space 3} .1069004
{txt}{space 10}retired  {c |}{col 20}{res}{space 2} .1189133{col 32}{space 2} .0971451{col 43}{space 1}    1.22{col 52}{space 3}0.222{col 60}{space 4}-.0722803{col 73}{space 3} .3101068
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2} .1323827{col 32}{space 2} .2079327{col 43}{space 1}    0.64{col 52}{space 3}0.525{col 60}{space 4}-.2766555{col 73}{space 3} .5414208
{txt}{space 6}not working  {c |}{col 20}{res}{space 2}-.0077289{col 32}{space 2} .1303547{col 43}{space 1}   -0.06{col 52}{space 3}0.953{col 60}{space 4}-.2650302{col 73}{space 3} .2495723
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2}-.1687038{col 32}{space 2} .3784406{col 43}{space 1}   -0.45{col 52}{space 3}0.656{col 60}{space 4}-.9126871{col 73}{space 3} .5752795
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .3201154{col 32}{space 2} .0537043{col 43}{space 1}    5.96{col 52}{space 3}0.000{col 60}{space 4} .2141758{col 73}{space 3} .4260551
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .3229518{col 32}{space 2} .1218744{col 43}{space 1}    2.65{col 52}{space 3}0.009{col 60}{space 4} .0823326{col 73}{space 3}  .563571
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 1.734728{col 32}{space 2} .6115635{col 43}{space 1}    2.84{col 52}{space 3}0.005{col 60}{space 4} .5287859{col 73}{space 3} 2.940669
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHblack threat4 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest if treatment==0 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       418

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res}  419.70676
{txt}{col 1}Number of PSUs{col 19}= {res}      418
{txt}{col 49}Average RVI{col 67}= {res}    0.1268
{txt}{col 49}Largest FMI{col 67}= {res}    0.2921
{txt}{col 49}Complete DF{col 67}= {res}       417
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}     83.50
{txt}{col 49}        avg{col 67}= {res}    244.60
{txt}{col 49}        max{col 67}= {res}    387.42
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  15{txt},{res}  398.8{txt}){col 67}= {res}     12.43
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           GHblack{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat4 {c |}{col 20}{res}{space 2} .2024612{col 32}{space 2} .0323143{col 43}{space 1}    6.27{col 52}{space 3}0.000{col 60}{space 4} .1387191{col 73}{space 3} .2662033
{txt}{space 12}female {c |}{col 20}{res}{space 2}-.0925422{col 32}{space 2} .0534416{col 43}{space 1}   -1.73{col 52}{space 3}0.084{col 60}{space 4}-.1976886{col 73}{space 3} .0126042
{txt}{space 15}Age {c |}{col 20}{res}{space 2}-.0036351{col 32}{space 2} .0031677{col 43}{space 1}   -1.15{col 52}{space 3}0.253{col 60}{space 4}-.0098848{col 73}{space 3} .0026145
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0087287{col 32}{space 2} .0184394{col 43}{space 1}   -0.47{col 52}{space 3}0.637{col 60}{space 4}-.0454006{col 73}{space 3} .0279433
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2} .0026175{col 32}{space 2} .0672408{col 43}{space 1}    0.04{col 52}{space 3}0.969{col 60}{space 4}-.1297188{col 73}{space 3} .1349538
{txt}{space 15}C2  {c |}{col 20}{res}{space 2} .0057141{col 32}{space 2} .0892947{col 43}{space 1}    0.06{col 52}{space 3}0.949{col 60}{space 4}-.1698689{col 73}{space 3}  .181297
{txt}{space 15}DE  {c |}{col 20}{res}{space 2}-.0489362{col 32}{space 2} .0890625{col 43}{space 1}   -0.55{col 52}{space 3}0.583{col 60}{space 4}-.2247061{col 73}{space 3} .1268338
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2}-.1228002{col 32}{space 2} .0839015{col 43}{space 1}   -1.46{col 52}{space 3}0.144{col 60}{space 4}-.2878263{col 73}{space 3} .0422259
{txt}full time student  {c |}{col 20}{res}{space 2}-.1003928{col 32}{space 2} .1419922{col 43}{space 1}   -0.71{col 52}{space 3}0.480{col 60}{space 4}-.3797846{col 73}{space 3} .1789991
{txt}{space 10}retired  {c |}{col 20}{res}{space 2} .1168227{col 32}{space 2} .0941578{col 43}{space 1}    1.24{col 52}{space 3}0.216{col 60}{space 4}-.0685073{col 73}{space 3} .3021528
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2} .1424748{col 32}{space 2} .1954575{col 43}{space 1}    0.73{col 52}{space 3}0.467{col 60}{space 4}-.2420719{col 73}{space 3} .5270215
{txt}{space 6}not working  {c |}{col 20}{res}{space 2}-.0132786{col 32}{space 2} .1329761{col 43}{space 1}   -0.10{col 52}{space 3}0.921{col 60}{space 4}-.2757053{col 73}{space 3} .2491481
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2}-.4725976{col 32}{space 2} .2883647{col 43}{space 1}   -1.64{col 52}{space 3}0.102{col 60}{space 4}-1.039553{col 73}{space 3}  .094358
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .2946309{col 32}{space 2} .0536194{col 43}{space 1}    5.49{col 52}{space 3}0.000{col 60}{space 4} .1888054{col 73}{space 3} .4004563
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .2420784{col 32}{space 2} .1185687{col 43}{space 1}    2.04{col 52}{space 3}0.043{col 60}{space 4} .0079063{col 73}{space 3} .4762505
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 1.626383{col 32}{space 2} .5156185{col 43}{space 1}    3.15{col 52}{space 3}0.002{col 60}{space 4} .6071051{col 73}{space 3} 2.645662
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHblack threat5 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest if treatment==0 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       419

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 420.914422
{txt}{col 1}Number of PSUs{col 19}= {res}      419
{txt}{col 49}Average RVI{col 67}= {res}    0.1158
{txt}{col 49}Largest FMI{col 67}= {res}    0.2409
{txt}{col 49}Complete DF{col 67}= {res}       418
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    110.44
{txt}{col 49}        avg{col 67}= {res}    259.04
{txt}{col 49}        max{col 67}= {res}    395.64
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  15{txt},{res}  401.8{txt}){col 67}= {res}      7.66
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           GHblack{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat5 {c |}{col 20}{res}{space 2}  .026635{col 32}{space 2} .0429819{col 43}{space 1}    0.62{col 52}{space 3}0.536{col 60}{space 4}-.0580239{col 73}{space 3} .1112939
{txt}{space 12}female {c |}{col 20}{res}{space 2}-.0878978{col 32}{space 2} .0569624{col 43}{space 1}   -1.54{col 52}{space 3}0.124{col 60}{space 4}-.1999754{col 73}{space 3} .0241799
{txt}{space 15}Age {c |}{col 20}{res}{space 2}-.0025355{col 32}{space 2} .0032753{col 43}{space 1}   -0.77{col 52}{space 3}0.440{col 60}{space 4}-.0089965{col 73}{space 3} .0039255
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0293149{col 32}{space 2} .0188928{col 43}{space 1}   -1.55{col 52}{space 3}0.124{col 60}{space 4}-.0667544{col 73}{space 3} .0081245
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2} .0514719{col 32}{space 2} .0708818{col 43}{space 1}    0.73{col 52}{space 3}0.468{col 60}{space 4}-.0880473{col 73}{space 3} .1909911
{txt}{space 15}C2  {c |}{col 20}{res}{space 2}-.0057448{col 32}{space 2} .0967099{col 43}{space 1}   -0.06{col 52}{space 3}0.953{col 60}{space 4}-.1958998{col 73}{space 3} .1844102
{txt}{space 15}DE  {c |}{col 20}{res}{space 2}-.0214909{col 32}{space 2}  .088907{col 43}{space 1}   -0.24{col 52}{space 3}0.809{col 60}{space 4}-.1970089{col 73}{space 3}  .154027
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2}-.1546668{col 32}{space 2} .0854436{col 43}{space 1}   -1.81{col 52}{space 3}0.071{col 60}{space 4}-.3227128{col 73}{space 3} .0133791
{txt}full time student  {c |}{col 20}{res}{space 2}-.2005678{col 32}{space 2} .1577393{col 43}{space 1}   -1.27{col 52}{space 3}0.204{col 60}{space 4}-.5108511{col 73}{space 3} .1097156
{txt}{space 10}retired  {c |}{col 20}{res}{space 2} .1102651{col 32}{space 2} .0976948{col 43}{space 1}    1.13{col 52}{space 3}0.260{col 60}{space 4}-.0820119{col 73}{space 3} .3025422
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2} .0933288{col 32}{space 2} .2088002{col 43}{space 1}    0.45{col 52}{space 3}0.655{col 60}{space 4}-.3174023{col 73}{space 3}   .50406
{txt}{space 6}not working  {c |}{col 20}{res}{space 2} -.025999{col 32}{space 2}  .129567{col 43}{space 1}   -0.20{col 52}{space 3}0.841{col 60}{space 4}-.2817323{col 73}{space 3} .2297342
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2}-.2204669{col 32}{space 2} .3628016{col 43}{space 1}   -0.61{col 52}{space 3}0.544{col 60}{space 4}-.9337268{col 73}{space 3} .4927931
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .3379279{col 32}{space 2} .0542135{col 43}{space 1}    6.23{col 52}{space 3}0.000{col 60}{space 4} .2310148{col 73}{space 3} .4448409
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .3330259{col 32}{space 2} .1224191{col 43}{space 1}    2.72{col 52}{space 3}0.007{col 60}{space 4} .0911829{col 73}{space 3} .5748689
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 2.097332{col 32}{space 2} .5958359{col 43}{space 1}    3.52{col 52}{space 3}0.001{col 60}{space 4} .9231694{col 73}{space 3} 3.271494
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. mi estimate: svy: reg GHMus threat1 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest if treatment==0 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       412

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 414.439681
{txt}{col 1}Number of PSUs{col 19}= {res}      412
{txt}{col 49}Average RVI{col 67}= {res}    0.1116
{txt}{col 49}Largest FMI{col 67}= {res}    0.2089
{txt}{col 49}Complete DF{col 67}= {res}       411
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    132.56
{txt}{col 49}        avg{col 67}= {res}    275.37
{txt}{col 49}        max{col 67}= {res}    397.24
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  15{txt},{res}  395.5{txt}){col 67}= {res}      8.40
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}             GHMus{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat1 {c |}{col 20}{res}{space 2}   .15739{col 32}{space 2} .0451005{col 43}{space 1}    3.49{col 52}{space 3}0.001{col 60}{space 4} .0686243{col 73}{space 3} .2461558
{txt}{space 12}female {c |}{col 20}{res}{space 2}-.0788104{col 32}{space 2} .0703274{col 43}{space 1}   -1.12{col 52}{space 3}0.263{col 60}{space 4}-.2172817{col 73}{space 3}  .059661
{txt}{space 15}Age {c |}{col 20}{res}{space 2}-.0024133{col 32}{space 2}  .003236{col 43}{space 1}   -0.75{col 52}{space 3}0.456{col 60}{space 4}-.0087792{col 73}{space 3} .0039525
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0604294{col 32}{space 2} .0221677{col 43}{space 1}   -2.73{col 52}{space 3}0.007{col 60}{space 4}-.1040894{col 73}{space 3}-.0167694
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2}-.1436703{col 32}{space 2} .0802863{col 43}{space 1}   -1.79{col 52}{space 3}0.074{col 60}{space 4}-.3016076{col 73}{space 3} .0142671
{txt}{space 15}C2  {c |}{col 20}{res}{space 2}-.0555077{col 32}{space 2} .1098039{col 43}{space 1}   -0.51{col 52}{space 3}0.614{col 60}{space 4}-.2714923{col 73}{space 3}  .160477
{txt}{space 15}DE  {c |}{col 20}{res}{space 2}-.0800412{col 32}{space 2} .1134632{col 43}{space 1}   -0.71{col 52}{space 3}0.481{col 60}{space 4}-.3034122{col 73}{space 3} .1433297
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2}-.1229641{col 32}{space 2} .0982051{col 43}{space 1}   -1.25{col 52}{space 3}0.212{col 60}{space 4}-.3162423{col 73}{space 3} .0703142
{txt}full time student  {c |}{col 20}{res}{space 2}-.0825783{col 32}{space 2} .2116188{col 43}{space 1}   -0.39{col 52}{space 3}0.697{col 60}{space 4}-.4994353{col 73}{space 3} .3342788
{txt}{space 10}retired  {c |}{col 20}{res}{space 2} .1193542{col 32}{space 2} .1103811{col 43}{space 1}    1.08{col 52}{space 3}0.280{col 60}{space 4}-.0978114{col 73}{space 3} .3365198
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2} .0083975{col 32}{space 2}  .211473{col 43}{space 1}    0.04{col 52}{space 3}0.968{col 60}{space 4}-.4079613{col 73}{space 3} .4247562
{txt}{space 6}not working  {c |}{col 20}{res}{space 2} -.014237{col 32}{space 2} .1372397{col 43}{space 1}   -0.10{col 52}{space 3}0.918{col 60}{space 4}-.2854038{col 73}{space 3} .2569298
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2}  .188147{col 32}{space 2} .5905729{col 43}{space 1}    0.32{col 52}{space 3}0.750{col 60}{space 4}-.9728921{col 73}{space 3} 1.349186
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .2216127{col 32}{space 2} .0597214{col 43}{space 1}    3.71{col 52}{space 3}0.000{col 60}{space 4} .1038782{col 73}{space 3} .3393472
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .3792352{col 32}{space 2} .1369778{col 43}{space 1}    2.77{col 52}{space 3}0.006{col 60}{space 4} .1082902{col 73}{space 3} .6501803
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 2.379665{col 32}{space 2} .7935277{col 43}{space 1}    3.00{col 52}{space 3}0.003{col 60}{space 4} .8184677{col 73}{space 3} 3.940863
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHMus threat2 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest if treatment==0 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       414

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 416.439681
{txt}{col 1}Number of PSUs{col 19}= {res}      414
{txt}{col 49}Average RVI{col 67}= {res}    0.1152
{txt}{col 49}Largest FMI{col 67}= {res}    0.2246
{txt}{col 49}Complete DF{col 67}= {res}       413
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    120.94
{txt}{col 49}        avg{col 67}= {res}    278.07
{txt}{col 49}        max{col 67}= {res}    400.41
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  15{txt},{res}  396.4{txt}){col 67}= {res}      7.48
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}             GHMus{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat2 {c |}{col 20}{res}{space 2} .0902853{col 32}{space 2} .0502981{col 43}{space 1}    1.80{col 52}{space 3}0.074{col 60}{space 4}-.0088754{col 73}{space 3}  .189446
{txt}{space 12}female {c |}{col 20}{res}{space 2} -.062384{col 32}{space 2} .0697947{col 43}{space 1}   -0.89{col 52}{space 3}0.372{col 60}{space 4}-.1997742{col 73}{space 3} .0750062
{txt}{space 15}Age {c |}{col 20}{res}{space 2}  -.00238{col 32}{space 2} .0033846{col 43}{space 1}   -0.70{col 52}{space 3}0.482{col 60}{space 4}-.0090371{col 73}{space 3} .0042771
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0657472{col 32}{space 2} .0220841{col 43}{space 1}   -2.98{col 52}{space 3}0.003{col 60}{space 4}-.1092277{col 73}{space 3}-.0222667
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2} -.136239{col 32}{space 2} .0823081{col 43}{space 1}   -1.66{col 52}{space 3}0.099{col 60}{space 4}-.2981359{col 73}{space 3} .0256579
{txt}{space 15}C2  {c |}{col 20}{res}{space 2}-.0436144{col 32}{space 2} .1114522{col 43}{space 1}   -0.39{col 52}{space 3}0.696{col 60}{space 4}-.2628257{col 73}{space 3} .1755969
{txt}{space 15}DE  {c |}{col 20}{res}{space 2}-.0630365{col 32}{space 2} .1098383{col 43}{space 1}   -0.57{col 52}{space 3}0.567{col 60}{space 4}-.2792756{col 73}{space 3} .1532025
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2}-.1555252{col 32}{space 2} .1008782{col 43}{space 1}   -1.54{col 52}{space 3}0.124{col 60}{space 4}-.3540205{col 73}{space 3} .0429701
{txt}full time student  {c |}{col 20}{res}{space 2}-.1407325{col 32}{space 2} .2260029{col 43}{space 1}   -0.62{col 52}{space 3}0.534{col 60}{space 4} -.585714{col 73}{space 3}  .304249
{txt}{space 10}retired  {c |}{col 20}{res}{space 2} .1154232{col 32}{space 2} .1114702{col 43}{space 1}    1.04{col 52}{space 3}0.301{col 60}{space 4}-.1038471{col 73}{space 3} .3346935
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2}-.0800225{col 32}{space 2} .2195322{col 43}{space 1}   -0.36{col 52}{space 3}0.716{col 60}{space 4}-.5121824{col 73}{space 3} .3521374
{txt}{space 6}not working  {c |}{col 20}{res}{space 2}-.0415859{col 32}{space 2} .1380469{col 43}{space 1}   -0.30{col 52}{space 3}0.764{col 60}{space 4}-.3143408{col 73}{space 3} .2311691
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2} .1444364{col 32}{space 2} .6147312{col 43}{space 1}    0.23{col 52}{space 3}0.814{col 60}{space 4}-1.064067{col 73}{space 3}  1.35294
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .2455803{col 32}{space 2} .0604774{col 43}{space 1}    4.06{col 52}{space 3}0.000{col 60}{space 4} .1263252{col 73}{space 3} .3648355
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .4355134{col 32}{space 2} .1383835{col 43}{space 1}    3.15{col 52}{space 3}0.002{col 60}{space 4} .1615454{col 73}{space 3} .7094814
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 2.564503{col 32}{space 2} .8272634{col 43}{space 1}    3.10{col 52}{space 3}0.002{col 60}{space 4} .9371635{col 73}{space 3} 4.191843
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHMus threat3 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest if treatment==0 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       414

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 416.439681
{txt}{col 1}Number of PSUs{col 19}= {res}      414
{txt}{col 49}Average RVI{col 67}= {res}    0.1113
{txt}{col 49}Largest FMI{col 67}= {res}    0.2290
{txt}{col 49}Complete DF{col 67}= {res}       413
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    117.84
{txt}{col 49}        avg{col 67}= {res}    283.35
{txt}{col 49}        max{col 67}= {res}    401.68
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  15{txt},{res}  397.5{txt}){col 67}= {res}      9.07
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}             GHMus{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat3 {c |}{col 20}{res}{space 2}  .171793{col 32}{space 2} .0431498{col 43}{space 1}    3.98{col 52}{space 3}0.000{col 60}{space 4} .0869158{col 73}{space 3} .2566701
{txt}{space 12}female {c |}{col 20}{res}{space 2}-.0929999{col 32}{space 2} .0714675{col 43}{space 1}   -1.30{col 52}{space 3}0.194{col 60}{space 4}-.2336531{col 73}{space 3} .0476533
{txt}{space 15}Age {c |}{col 20}{res}{space 2} -.003024{col 32}{space 2} .0032767{col 43}{space 1}   -0.92{col 52}{space 3}0.357{col 60}{space 4}-.0094691{col 73}{space 3}  .003421
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0577194{col 32}{space 2} .0220544{col 43}{space 1}   -2.62{col 52}{space 3}0.009{col 60}{space 4}-.1011519{col 73}{space 3}-.0142868
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2} -.134558{col 32}{space 2} .0803328{col 43}{space 1}   -1.68{col 52}{space 3}0.095{col 60}{space 4}-.2925837{col 73}{space 3} .0234678
{txt}{space 15}C2  {c |}{col 20}{res}{space 2}-.0546238{col 32}{space 2} .1076158{col 43}{space 1}   -0.51{col 52}{space 3}0.612{col 60}{space 4}-.2663021{col 73}{space 3} .1570544
{txt}{space 15}DE  {c |}{col 20}{res}{space 2}-.0898679{col 32}{space 2} .1111136{col 43}{space 1}   -0.81{col 52}{space 3}0.419{col 60}{space 4}-.3086248{col 73}{space 3} .1288891
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2}-.1196248{col 32}{space 2} .1005632{col 43}{space 1}   -1.19{col 52}{space 3}0.235{col 60}{space 4}-.3175052{col 73}{space 3} .0782556
{txt}full time student  {c |}{col 20}{res}{space 2}-.0903269{col 32}{space 2} .2127335{col 43}{space 1}   -0.42{col 52}{space 3}0.672{col 60}{space 4}-.5093572{col 73}{space 3} .3287035
{txt}{space 10}retired  {c |}{col 20}{res}{space 2} .0988047{col 32}{space 2} .1089974{col 43}{space 1}    0.91{col 52}{space 3}0.365{col 60}{space 4}-.1156291{col 73}{space 3} .3132385
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2}-.0192194{col 32}{space 2} .2166407{col 43}{space 1}   -0.09{col 52}{space 3}0.929{col 60}{space 4}-.4457067{col 73}{space 3} .4072679
{txt}{space 6}not working  {c |}{col 20}{res}{space 2}-.0081336{col 32}{space 2} .1356364{col 43}{space 1}   -0.06{col 52}{space 3}0.952{col 60}{space 4}  -.27608{col 73}{space 3} .2598128
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2} .2282071{col 32}{space 2} .6422684{col 43}{space 1}    0.36{col 52}{space 3}0.723{col 60}{space 4} -1.03442{col 73}{space 3} 1.490835
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .2203915{col 32}{space 2} .0594995{col 43}{space 1}    3.70{col 52}{space 3}0.000{col 60}{space 4} .1031169{col 73}{space 3} .3376662
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .4236901{col 32}{space 2} .1350903{col 43}{space 1}    3.14{col 52}{space 3}0.002{col 60}{space 4} .1561708{col 73}{space 3} .6912094
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 2.212135{col 32}{space 2} .8326451{col 43}{space 1}    2.66{col 52}{space 3}0.008{col 60}{space 4} .5741339{col 73}{space 3} 3.850136
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHMus threat4 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest if treatment==0 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       415

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 417.232018
{txt}{col 1}Number of PSUs{col 19}= {res}      415
{txt}{col 49}Average RVI{col 67}= {res}    0.1283
{txt}{col 49}Largest FMI{col 67}= {res}    0.2295
{txt}{col 49}Complete DF{col 67}= {res}       414
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    117.60
{txt}{col 49}        avg{col 67}= {res}    254.82
{txt}{col 49}        max{col 67}= {res}    392.13
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  15{txt},{res}  394.9{txt}){col 67}= {res}     15.14
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}             GHMus{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat4 {c |}{col 20}{res}{space 2} .3146162{col 32}{space 2}  .038333{col 43}{space 1}    8.21{col 52}{space 3}0.000{col 60}{space 4} .2388926{col 73}{space 3} .3903398
{txt}{space 12}female {c |}{col 20}{res}{space 2}-.0530766{col 32}{space 2} .0629516{col 43}{space 1}   -0.84{col 52}{space 3}0.400{col 60}{space 4}-.1770332{col 73}{space 3}   .07088
{txt}{space 15}Age {c |}{col 20}{res}{space 2}-.0042419{col 32}{space 2} .0031435{col 43}{space 1}   -1.35{col 52}{space 3}0.178{col 60}{space 4}-.0104245{col 73}{space 3} .0019408
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0401444{col 32}{space 2} .0194328{col 43}{space 1}   -2.07{col 52}{space 3}0.040{col 60}{space 4}-.0784408{col 73}{space 3} -.001848
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2}-.2027162{col 32}{space 2} .0765819{col 43}{space 1}   -2.65{col 52}{space 3}0.009{col 60}{space 4}-.3534169{col 73}{space 3}-.0520155
{txt}{space 15}C2  {c |}{col 20}{res}{space 2}-.0309224{col 32}{space 2} .0945707{col 43}{space 1}   -0.33{col 52}{space 3}0.744{col 60}{space 4}-.2170036{col 73}{space 3} .1551587
{txt}{space 15}DE  {c |}{col 20}{res}{space 2} -.113213{col 32}{space 2} .1054854{col 43}{space 1}   -1.07{col 52}{space 3}0.284{col 60}{space 4}-.3209821{col 73}{space 3} .0945562
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2}-.1114827{col 32}{space 2} .0932329{col 43}{space 1}   -1.20{col 52}{space 3}0.233{col 60}{space 4} -.294964{col 73}{space 3} .0719987
{txt}full time student  {c |}{col 20}{res}{space 2} .0528014{col 32}{space 2}  .211388{col 43}{space 1}    0.25{col 52}{space 3}0.803{col 60}{space 4}-.3636051{col 73}{space 3}  .469208
{txt}{space 10}retired  {c |}{col 20}{res}{space 2} .1122349{col 32}{space 2} .1018702{col 43}{space 1}    1.10{col 52}{space 3}0.271{col 60}{space 4}-.0882164{col 73}{space 3} .3126861
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2}-.0250634{col 32}{space 2} .1974797{col 43}{space 1}   -0.13{col 52}{space 3}0.899{col 60}{space 4}-.4140355{col 73}{space 3} .3639087
{txt}{space 6}not working  {c |}{col 20}{res}{space 2} -.039003{col 32}{space 2} .1353528{col 43}{space 1}   -0.29{col 52}{space 3}0.774{col 60}{space 4}-.3063377{col 73}{space 3} .2283318
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2}-.4094215{col 32}{space 2} .4857981{col 43}{space 1}   -0.84{col 52}{space 3}0.400{col 60}{space 4}-1.364516{col 73}{space 3} .5456731
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .1708874{col 32}{space 2} .0574315{col 43}{space 1}    2.98{col 52}{space 3}0.003{col 60}{space 4} .0574198{col 73}{space 3} .2843549
{txt}{space 11}selfest {c |}{col 20}{res}{space 2}  .309448{col 32}{space 2} .1295688{col 43}{space 1}    2.39{col 52}{space 3}0.019{col 60}{space 4} .0528574{col 73}{space 3} .5660387
{txt}{space 13}_cons {c |}{col 20}{res}{space 2}  2.26454{col 32}{space 2}  .660411{col 43}{space 1}    3.43{col 52}{space 3}0.001{col 60}{space 4} .9652765{col 73}{space 3} 3.563803
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHMus threat5 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest if treatment==0 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       416

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 418.439681
{txt}{col 1}Number of PSUs{col 19}= {res}      416
{txt}{col 49}Average RVI{col 67}= {res}    0.1035
{txt}{col 49}Largest FMI{col 67}= {res}    0.2114
{txt}{col 49}Complete DF{col 67}= {res}       415
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    131.03
{txt}{col 49}        avg{col 67}= {res}    288.08
{txt}{col 49}        max{col 67}= {res}    402.04
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  15{txt},{res}  400.7{txt}){col 67}= {res}      7.13
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}             GHMus{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat5 {c |}{col 20}{res}{space 2} .0091935{col 32}{space 2} .0564666{col 43}{space 1}    0.16{col 52}{space 3}0.871{col 60}{space 4} -.101838{col 73}{space 3}  .120225
{txt}{space 12}female {c |}{col 20}{res}{space 2}-.0472671{col 32}{space 2} .0710094{col 43}{space 1}   -0.67{col 52}{space 3}0.506{col 60}{space 4}-.1870222{col 73}{space 3}  .092488
{txt}{space 15}Age {c |}{col 20}{res}{space 2}-.0024814{col 32}{space 2}  .003349{col 43}{space 1}   -0.74{col 52}{space 3}0.459{col 60}{space 4}-.0090686{col 73}{space 3} .0041058
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0711962{col 32}{space 2} .0221894{col 43}{space 1}   -3.21{col 52}{space 3}0.001{col 60}{space 4}-.1148797{col 73}{space 3}-.0275127
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2}-.1361249{col 32}{space 2} .0823972{col 43}{space 1}   -1.65{col 52}{space 3}0.099{col 60}{space 4}-.2981876{col 73}{space 3} .0259379
{txt}{space 15}C2  {c |}{col 20}{res}{space 2}-.0441015{col 32}{space 2} .1113126{col 43}{space 1}   -0.40{col 52}{space 3}0.692{col 60}{space 4}-.2630473{col 73}{space 3} .1748443
{txt}{space 15}DE  {c |}{col 20}{res}{space 2}-.0523995{col 32}{space 2}  .110675{col 43}{space 1}   -0.47{col 52}{space 3}0.636{col 60}{space 4}-.2703167{col 73}{space 3} .1655177
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2}-.1606858{col 32}{space 2} .0983023{col 43}{space 1}   -1.63{col 52}{space 3}0.103{col 60}{space 4}-.3541611{col 73}{space 3} .0327895
{txt}full time student  {c |}{col 20}{res}{space 2}-.1277853{col 32}{space 2} .2206882{col 43}{space 1}   -0.58{col 52}{space 3}0.563{col 60}{space 4}-.5623944{col 73}{space 3} .3068238
{txt}{space 10}retired  {c |}{col 20}{res}{space 2} .0986514{col 32}{space 2} .1114543{col 43}{space 1}    0.89{col 52}{space 3}0.377{col 60}{space 4}-.1206526{col 73}{space 3} .3179554
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2}-.0959033{col 32}{space 2} .2162309{col 43}{space 1}   -0.44{col 52}{space 3}0.658{col 60}{space 4}-.5215692{col 73}{space 3} .3297625
{txt}{space 6}not working  {c |}{col 20}{res}{space 2}-.0323406{col 32}{space 2} .1378613{col 43}{space 1}   -0.23{col 52}{space 3}0.815{col 60}{space 4}-.3048154{col 73}{space 3} .2401341
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2} .1608742{col 32}{space 2} .6184971{col 43}{space 1}    0.26{col 52}{space 3}0.795{col 60}{space 4}-1.055018{col 73}{space 3} 1.376767
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .2365956{col 32}{space 2} .0598103{col 43}{space 1}    3.96{col 52}{space 3}0.000{col 60}{space 4}  .118671{col 73}{space 3} .3545202
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .4652096{col 32}{space 2} .1393673{col 43}{space 1}    3.34{col 52}{space 3}0.001{col 60}{space 4} .1895085{col 73}{space 3} .7409107
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 2.899224{col 32}{space 2} .8315298{col 43}{space 1}    3.49{col 52}{space 3}0.001{col 60}{space 4} 1.263994{col 73}{space 3} 4.534454
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. mi estimate: svy: reg GHEEur threat1 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest if treatment==0 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       410

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res}  412.50712
{txt}{col 1}Number of PSUs{col 19}= {res}      410
{txt}{col 49}Average RVI{col 67}= {res}    0.1831
{txt}{col 49}Largest FMI{col 67}= {res}    0.3578
{txt}{col 49}Complete DF{col 67}= {res}       409
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}     60.33
{txt}{col 49}        avg{col 67}= {res}    219.62
{txt}{col 49}        max{col 67}= {res}    339.70
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  15{txt},{res}  376.1{txt}){col 67}= {res}      8.32
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}            GHEEur{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat1 {c |}{col 20}{res}{space 2} .0947823{col 32}{space 2}  .040253{col 43}{space 1}    2.35{col 52}{space 3}0.020{col 60}{space 4} .0153254{col 73}{space 3} .1742392
{txt}{space 12}female {c |}{col 20}{res}{space 2}-.0415982{col 32}{space 2} .0597445{col 43}{space 1}   -0.70{col 52}{space 3}0.487{col 60}{space 4}-.1593391{col 73}{space 3} .0761426
{txt}{space 15}Age {c |}{col 20}{res}{space 2}-.0033623{col 32}{space 2} .0030849{col 43}{space 1}   -1.09{col 52}{space 3}0.277{col 60}{space 4}-.0094308{col 73}{space 3} .0027063
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0703038{col 32}{space 2} .0176855{col 43}{space 1}   -3.98{col 52}{space 3}0.000{col 60}{space 4}-.1051402{col 73}{space 3}-.0354673
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2}-.0359445{col 32}{space 2} .0680172{col 43}{space 1}   -0.53{col 52}{space 3}0.598{col 60}{space 4} -.169781{col 73}{space 3} .0978921
{txt}{space 15}C2  {c |}{col 20}{res}{space 2} .0248435{col 32}{space 2} .1022861{col 43}{space 1}    0.24{col 52}{space 3}0.808{col 60}{space 4}-.1764981{col 73}{space 3} .2261851
{txt}{space 15}DE  {c |}{col 20}{res}{space 2}-.0287066{col 32}{space 2} .0908596{col 43}{space 1}   -0.32{col 52}{space 3}0.752{col 60}{space 4} -.207547{col 73}{space 3} .1501338
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2}-.1475811{col 32}{space 2} .0915057{col 43}{space 1}   -1.61{col 52}{space 3}0.109{col 60}{space 4}-.3284223{col 73}{space 3}   .03326
{txt}full time student  {c |}{col 20}{res}{space 2}-.2256009{col 32}{space 2} .1985498{col 43}{space 1}   -1.14{col 52}{space 3}0.260{col 60}{space 4}-.6227151{col 73}{space 3} .1715132
{txt}{space 10}retired  {c |}{col 20}{res}{space 2} .0917488{col 32}{space 2} .0968724{col 43}{space 1}    0.95{col 52}{space 3}0.344{col 60}{space 4}-.0987966{col 73}{space 3} .2822941
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2}-.0251516{col 32}{space 2} .2218975{col 43}{space 1}   -0.11{col 52}{space 3}0.910{col 60}{space 4}-.4617478{col 73}{space 3} .4114445
{txt}{space 6}not working  {c |}{col 20}{res}{space 2}-.0028216{col 32}{space 2} .1459948{col 43}{space 1}   -0.02{col 52}{space 3}0.985{col 60}{space 4}-.2914964{col 73}{space 3} .2858533
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2}-.2448503{col 32}{space 2} .1347079{col 43}{space 1}   -1.82{col 52}{space 3}0.070{col 60}{space 4}-.5101857{col 73}{space 3}  .020485
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2}  .194532{col 32}{space 2} .0580824{col 43}{space 1}    3.35{col 52}{space 3}0.001{col 60}{space 4} .0786662{col 73}{space 3} .3103977
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .2513842{col 32}{space 2} .1212394{col 43}{space 1}    2.07{col 52}{space 3}0.040{col 60}{space 4} .0115166{col 73}{space 3} .4912517
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 3.111596{col 32}{space 2} .4943689{col 43}{space 1}    6.29{col 52}{space 3}0.000{col 60}{space 4} 2.137605{col 73}{space 3} 4.085587
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHEEur threat2 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest if treatment==0 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       412

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res}  414.50712
{txt}{col 1}Number of PSUs{col 19}= {res}      412
{txt}{col 49}Average RVI{col 67}= {res}    0.1740
{txt}{col 49}Largest FMI{col 67}= {res}    0.3467
{txt}{col 49}Complete DF{col 67}= {res}       411
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}     63.58
{txt}{col 49}        avg{col 67}= {res}    221.24
{txt}{col 49}        max{col 67}= {res}    346.77
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  15{txt},{res}  380.0{txt}){col 67}= {res}      8.20
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}            GHEEur{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat2 {c |}{col 20}{res}{space 2} .0680243{col 32}{space 2} .0424341{col 43}{space 1}    1.60{col 52}{space 3}0.110{col 60}{space 4}-.0155782{col 73}{space 3} .1516269
{txt}{space 12}female {c |}{col 20}{res}{space 2}-.0289649{col 32}{space 2}  .059531{col 43}{space 1}   -0.49{col 52}{space 3}0.627{col 60}{space 4}-.1463018{col 73}{space 3}  .088372
{txt}{space 15}Age {c |}{col 20}{res}{space 2}-.0031454{col 32}{space 2} .0030892{col 43}{space 1}   -1.02{col 52}{space 3}0.309{col 60}{space 4}-.0092224{col 73}{space 3} .0029316
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2} -.075085{col 32}{space 2} .0182468{col 43}{space 1}   -4.11{col 52}{space 3}0.000{col 60}{space 4}-.1110382{col 73}{space 3}-.0391318
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2}-.0340354{col 32}{space 2} .0685367{col 43}{space 1}   -0.50{col 52}{space 3}0.620{col 60}{space 4}-.1688904{col 73}{space 3} .1008195
{txt}{space 15}C2  {c |}{col 20}{res}{space 2} .0318973{col 32}{space 2} .1032359{col 43}{space 1}    0.31{col 52}{space 3}0.758{col 60}{space 4}-.1713015{col 73}{space 3} .2350961
{txt}{space 15}DE  {c |}{col 20}{res}{space 2}-.0344758{col 32}{space 2} .0886381{col 43}{space 1}   -0.39{col 52}{space 3}0.698{col 60}{space 4}-.2088876{col 73}{space 3}  .139936
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2}-.1699396{col 32}{space 2} .0898329{col 43}{space 1}   -1.89{col 52}{space 3}0.060{col 60}{space 4}-.3473668{col 73}{space 3} .0074875
{txt}full time student  {c |}{col 20}{res}{space 2}-.2507112{col 32}{space 2} .2079022{col 43}{space 1}   -1.21{col 52}{space 3}0.232{col 60}{space 4} -.665658{col 73}{space 3} .1642357
{txt}{space 10}retired  {c |}{col 20}{res}{space 2}  .086426{col 32}{space 2} .0967658{col 43}{space 1}    0.89{col 52}{space 3}0.372{col 60}{space 4}-.1038956{col 73}{space 3} .2767477
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2} -.071743{col 32}{space 2} .2258226{col 43}{space 1}   -0.32{col 52}{space 3}0.751{col 60}{space 4}-.5160873{col 73}{space 3} .3726012
{txt}{space 6}not working  {c |}{col 20}{res}{space 2}-.0203363{col 32}{space 2} .1464371{col 43}{space 1}   -0.14{col 52}{space 3}0.890{col 60}{space 4}-.3098427{col 73}{space 3} .2691701
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2}-.2740627{col 32}{space 2} .1366387{col 43}{space 1}   -2.01{col 52}{space 3}0.046{col 60}{space 4}-.5431942{col 73}{space 3}-.0049313
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .2126817{col 32}{space 2} .0583354{col 43}{space 1}    3.65{col 52}{space 3}0.001{col 60}{space 4} .0961285{col 73}{space 3}  .329235
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .2872282{col 32}{space 2} .1216098{col 43}{space 1}    2.36{col 52}{space 3}0.020{col 60}{space 4} .0463741{col 73}{space 3} .5280822
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 3.197134{col 32}{space 2} .5278125{col 43}{space 1}    6.06{col 52}{space 3}0.000{col 60}{space 4} 2.155637{col 73}{space 3} 4.238632
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHEEur threat3 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest if treatment==0 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       412

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res}  414.50712
{txt}{col 1}Number of PSUs{col 19}= {res}      412
{txt}{col 49}Average RVI{col 67}= {res}    0.1847
{txt}{col 49}Largest FMI{col 67}= {res}    0.3927
{txt}{col 49}Complete DF{col 67}= {res}       411
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}     51.74
{txt}{col 49}        avg{col 67}= {res}    226.12
{txt}{col 49}        max{col 67}= {res}    339.07
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  15{txt},{res}  377.1{txt}){col 67}= {res}     10.45
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}            GHEEur{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat3 {c |}{col 20}{res}{space 2}  .138675{col 32}{space 2} .0381263{col 43}{space 1}    3.64{col 52}{space 3}0.000{col 60}{space 4} .0635627{col 73}{space 3} .2137874
{txt}{space 12}female {c |}{col 20}{res}{space 2}-.0612709{col 32}{space 2} .0602801{col 43}{space 1}   -1.02{col 52}{space 3}0.311{col 60}{space 4}-.1801161{col 73}{space 3} .0575742
{txt}{space 15}Age {c |}{col 20}{res}{space 2}-.0035181{col 32}{space 2} .0030071{col 43}{space 1}   -1.17{col 52}{space 3}0.243{col 60}{space 4}-.0094343{col 73}{space 3} .0023981
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0652615{col 32}{space 2} .0177356{col 43}{space 1}   -3.68{col 52}{space 3}0.000{col 60}{space 4} -.100184{col 73}{space 3}-.0303391
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2}-.0263869{col 32}{space 2} .0669566{col 43}{space 1}   -0.39{col 52}{space 3}0.694{col 60}{space 4}-.1581383{col 73}{space 3} .1053645
{txt}{space 15}C2  {c |}{col 20}{res}{space 2} .0273629{col 32}{space 2} .0992366{col 43}{space 1}    0.28{col 52}{space 3}0.783{col 60}{space 4}-.1679807{col 73}{space 3} .2227066
{txt}{space 15}DE  {c |}{col 20}{res}{space 2}-.0332526{col 32}{space 2} .0912085{col 43}{space 1}   -0.36{col 52}{space 3}0.716{col 60}{space 4} -.212765{col 73}{space 3} .1462598
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2}-.1415546{col 32}{space 2}  .091706{col 43}{space 1}   -1.54{col 52}{space 3}0.125{col 60}{space 4}-.3228098{col 73}{space 3} .0397005
{txt}full time student  {c |}{col 20}{res}{space 2} -.224036{col 32}{space 2} .1903986{col 43}{space 1}   -1.18{col 52}{space 3}0.245{col 60}{space 4}-.6061451{col 73}{space 3} .1580731
{txt}{space 10}retired  {c |}{col 20}{res}{space 2} .0755014{col 32}{space 2} .0962886{col 43}{space 1}    0.78{col 52}{space 3}0.434{col 60}{space 4}-.1138968{col 73}{space 3} .2648997
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2} -.036724{col 32}{space 2} .2207344{col 43}{space 1}   -0.17{col 52}{space 3}0.868{col 60}{space 4}-.4710206{col 73}{space 3} .3975726
{txt}{space 6}not working  {c |}{col 20}{res}{space 2} .0010178{col 32}{space 2} .1458852{col 43}{space 1}    0.01{col 52}{space 3}0.994{col 60}{space 4}-.2873411{col 73}{space 3} .2893766
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2}-.1980128{col 32}{space 2}  .133112{col 43}{space 1}   -1.49{col 52}{space 3}0.138{col 60}{space 4}-.4601728{col 73}{space 3} .0641472
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .1866558{col 32}{space 2} .0582304{col 43}{space 1}    3.21{col 52}{space 3}0.002{col 60}{space 4} .0704622{col 73}{space 3} .3028494
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .2879417{col 32}{space 2} .1180775{col 43}{space 1}    2.44{col 52}{space 3}0.016{col 60}{space 4} .0544884{col 73}{space 3} .5213951
{txt}{space 13}_cons {c |}{col 20}{res}{space 2}  2.83539{col 32}{space 2} .4950276{col 43}{space 1}    5.73{col 52}{space 3}0.000{col 60}{space 4} 1.860646{col 73}{space 3} 3.810134
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHEEur threat4 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest if treatment==0 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       413

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 415.299458
{txt}{col 1}Number of PSUs{col 19}= {res}      413
{txt}{col 49}Average RVI{col 67}= {res}    0.1823
{txt}{col 49}Largest FMI{col 67}= {res}    0.3497
{txt}{col 49}Complete DF{col 67}= {res}       412
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}     62.74
{txt}{col 49}        avg{col 67}= {res}    200.55
{txt}{col 49}        max{col 67}= {res}    330.57
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  15{txt},{res}  379.0{txt}){col 67}= {res}     10.11
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}            GHEEur{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat4 {c |}{col 20}{res}{space 2} .1990892{col 32}{space 2} .0339983{col 43}{space 1}    5.86{col 52}{space 3}0.000{col 60}{space 4}   .13195{col 73}{space 3} .2662285
{txt}{space 12}female {c |}{col 20}{res}{space 2}-.0299521{col 32}{space 2} .0570515{col 43}{space 1}   -0.53{col 52}{space 3}0.600{col 60}{space 4}-.1424507{col 73}{space 3} .0825465
{txt}{space 15}Age {c |}{col 20}{res}{space 2}-.0038443{col 32}{space 2} .0029843{col 43}{space 1}   -1.29{col 52}{space 3}0.199{col 60}{space 4}-.0097151{col 73}{space 3} .0020265
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0563464{col 32}{space 2} .0177273{col 43}{space 1}   -3.18{col 52}{space 3}0.002{col 60}{space 4}-.0912986{col 73}{space 3}-.0213942
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2}-.0691977{col 32}{space 2} .0651102{col 43}{space 1}   -1.06{col 52}{space 3}0.289{col 60}{space 4}-.1973835{col 73}{space 3} .0589881
{txt}{space 15}C2  {c |}{col 20}{res}{space 2} .0473265{col 32}{space 2} .0951335{col 43}{space 1}    0.50{col 52}{space 3}0.619{col 60}{space 4}-.1399555{col 73}{space 3} .2346085
{txt}{space 15}DE  {c |}{col 20}{res}{space 2}-.0561687{col 32}{space 2} .0891877{col 43}{space 1}   -0.63{col 52}{space 3}0.529{col 60}{space 4}-.2317053{col 73}{space 3} .1193678
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2}-.1542425{col 32}{space 2} .0902415{col 43}{space 1}   -1.71{col 52}{space 3}0.089{col 60}{space 4}-.3325226{col 73}{space 3} .0240377
{txt}full time student  {c |}{col 20}{res}{space 2}-.1800214{col 32}{space 2} .2077169{col 43}{space 1}   -0.87{col 52}{space 3}0.389{col 60}{space 4}-.5947894{col 73}{space 3} .2347465
{txt}{space 10}retired  {c |}{col 20}{res}{space 2} .0700944{col 32}{space 2} .0938218{col 43}{space 1}    0.75{col 52}{space 3}0.456{col 60}{space 4}-.1144688{col 73}{space 3} .2546575
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2}-.0339528{col 32}{space 2} .2077417{col 43}{space 1}   -0.16{col 52}{space 3}0.870{col 60}{space 4}-.4428388{col 73}{space 3} .3749333
{txt}{space 6}not working  {c |}{col 20}{res}{space 2}-.0122726{col 32}{space 2}  .143619{col 43}{space 1}   -0.09{col 52}{space 3}0.932{col 60}{space 4}-.2961503{col 73}{space 3} .2716052
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2}-.4604082{col 32}{space 2} .1242327{col 43}{space 1}   -3.71{col 52}{space 3}0.000{col 60}{space 4}-.7063074{col 73}{space 3}-.2145089
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2}  .166752{col 32}{space 2} .0571401{col 43}{space 1}    2.92{col 52}{space 3}0.005{col 60}{space 4} .0525574{col 73}{space 3} .2809466
{txt}{space 11}selfest {c |}{col 20}{res}{space 2}  .235276{col 32}{space 2} .1174533{col 43}{space 1}    2.00{col 52}{space 3}0.047{col 60}{space 4} .0029449{col 73}{space 3}  .467607
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 2.801046{col 32}{space 2} .4624962{col 43}{space 1}    6.06{col 52}{space 3}0.000{col 60}{space 4} 1.888415{col 73}{space 3} 3.713678
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHEEur threat5 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest if treatment==0 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       413

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res}  415.50712
{txt}{col 1}Number of PSUs{col 19}= {res}      413
{txt}{col 49}Average RVI{col 67}= {res}    0.1700
{txt}{col 49}Largest FMI{col 67}= {res}    0.3355
{txt}{col 49}Complete DF{col 67}= {res}       412
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}     67.09
{txt}{col 49}        avg{col 67}= {res}    234.04
{txt}{col 49}        max{col 67}= {res}    350.76
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  15{txt},{res}  382.4{txt}){col 67}= {res}      8.13
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}            GHEEur{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat5 {c |}{col 20}{res}{space 2}  .048581{col 32}{space 2} .0417025{col 43}{space 1}    1.16{col 52}{space 3}0.245{col 60}{space 4}-.0334374{col 73}{space 3} .1305995
{txt}{space 12}female {c |}{col 20}{res}{space 2}-.0306844{col 32}{space 2} .0604543{col 43}{space 1}   -0.51{col 52}{space 3}0.612{col 60}{space 4}-.1498933{col 73}{space 3} .0885245
{txt}{space 15}Age {c |}{col 20}{res}{space 2}-.0033123{col 32}{space 2} .0030674{col 43}{space 1}   -1.08{col 52}{space 3}0.281{col 60}{space 4}-.0093463{col 73}{space 3} .0027217
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0761295{col 32}{space 2} .0177998{col 43}{space 1}   -4.28{col 52}{space 3}0.000{col 60}{space 4}-.1111767{col 73}{space 3}-.0410823
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2}-.0265968{col 32}{space 2} .0684263{col 43}{space 1}   -0.39{col 52}{space 3}0.698{col 60}{space 4}-.1612328{col 73}{space 3} .1080393
{txt}{space 15}C2  {c |}{col 20}{res}{space 2} .0323004{col 32}{space 2} .1029093{col 43}{space 1}    0.31{col 52}{space 3}0.754{col 60}{space 4} -.170249{col 73}{space 3} .2348498
{txt}{space 15}DE  {c |}{col 20}{res}{space 2}-.0234095{col 32}{space 2} .0898318{col 43}{space 1}   -0.26{col 52}{space 3}0.795{col 60}{space 4}-.2002242{col 73}{space 3} .1534052
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2}-.1657779{col 32}{space 2} .0907831{col 43}{space 1}   -1.83{col 52}{space 3}0.070{col 60}{space 4}-.3451743{col 73}{space 3} .0136186
{txt}full time student  {c |}{col 20}{res}{space 2}-.2445124{col 32}{space 2} .2079192{col 43}{space 1}   -1.18{col 52}{space 3}0.244{col 60}{space 4}-.6595107{col 73}{space 3} .1704859
{txt}{space 10}retired  {c |}{col 20}{res}{space 2} .0900204{col 32}{space 2} .0972138{col 43}{space 1}    0.93{col 52}{space 3}0.355{col 60}{space 4}-.1012202{col 73}{space 3}  .281261
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2}-.0883885{col 32}{space 2} .2234369{col 43}{space 1}   -0.40{col 52}{space 3}0.693{col 60}{space 4} -.528037{col 73}{space 3} .3512601
{txt}{space 6}not working  {c |}{col 20}{res}{space 2}-.0097193{col 32}{space 2} .1461531{col 43}{space 1}   -0.07{col 52}{space 3}0.947{col 60}{space 4}-.2987065{col 73}{space 3} .2792678
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2}-.2737177{col 32}{space 2} .1357673{col 43}{space 1}   -2.02{col 52}{space 3}0.045{col 60}{space 4}-.5411353{col 73}{space 3}-.0063001
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .1965541{col 32}{space 2} .0590052{col 43}{space 1}    3.33{col 52}{space 3}0.001{col 60}{space 4} .0788656{col 73}{space 3} .3142426
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .3105522{col 32}{space 2} .1196011{col 43}{space 1}    2.60{col 52}{space 3}0.010{col 60}{space 4} .0740891{col 73}{space 3} .5470153
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 3.298832{col 32}{space 2} .4950764{col 43}{space 1}    6.66{col 52}{space 3}0.000{col 60}{space 4} 2.324063{col 73}{space 3}   4.2736
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. mi estimate: svy: reg GHwhite threat1 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest if treatment==0 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       404

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 408.603048
{txt}{col 1}Number of PSUs{col 19}= {res}      404
{txt}{col 49}Average RVI{col 67}= {res}    0.1366
{txt}{col 49}Largest FMI{col 67}= {res}    0.2636
{txt}{col 49}Complete DF{col 67}= {res}       403
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}     96.16
{txt}{col 49}        avg{col 67}= {res}    300.21
{txt}{col 49}        max{col 67}= {res}    386.01
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  15{txt},{res}  384.2{txt}){col 67}= {res}      1.97
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0162

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           GHwhite{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat1 {c |}{col 20}{res}{space 2} .1366531{col 32}{space 2} .0967291{col 43}{space 1}    1.41{col 52}{space 3}0.159{col 60}{space 4}-.0535517{col 73}{space 3}  .326858
{txt}{space 12}female {c |}{col 20}{res}{space 2} .3113204{col 32}{space 2} .1378955{col 43}{space 1}    2.26{col 52}{space 3}0.025{col 60}{space 4} .0401539{col 73}{space 3} .5824868
{txt}{space 15}Age {c |}{col 20}{res}{space 2}-.0186856{col 32}{space 2} .0081668{col 43}{space 1}   -2.29{col 52}{space 3}0.023{col 60}{space 4} -.034749{col 73}{space 3}-.0026222
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0406133{col 32}{space 2} .0499188{col 43}{space 1}   -0.81{col 52}{space 3}0.416{col 60}{space 4}-.1387948{col 73}{space 3} .0575682
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2}-.0589513{col 32}{space 2} .1670595{col 43}{space 1}   -0.35{col 52}{space 3}0.724{col 60}{space 4}-.3876184{col 73}{space 3} .2697159
{txt}{space 15}C2  {c |}{col 20}{res}{space 2} .1544827{col 32}{space 2} .2606738{col 43}{space 1}    0.59{col 52}{space 3}0.554{col 60}{space 4}-.3583858{col 73}{space 3} .6673513
{txt}{space 15}DE  {c |}{col 20}{res}{space 2} .0982761{col 32}{space 2} .2354884{col 43}{space 1}    0.42{col 52}{space 3}0.677{col 60}{space 4}-.3650746{col 73}{space 3} .5616268
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2}-.0052524{col 32}{space 2}  .220861{col 43}{space 1}   -0.02{col 52}{space 3}0.981{col 60}{space 4}-.4394935{col 73}{space 3} .4289887
{txt}full time student  {c |}{col 20}{res}{space 2}  .516973{col 32}{space 2} .4020858{col 43}{space 1}    1.29{col 52}{space 3}0.200{col 60}{space 4}-.2753358{col 73}{space 3} 1.309282
{txt}{space 10}retired  {c |}{col 20}{res}{space 2} .3034972{col 32}{space 2} .2367063{col 43}{space 1}    1.28{col 52}{space 3}0.201{col 60}{space 4}-.1623196{col 73}{space 3}  .769314
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2} .0703361{col 32}{space 2} .2561992{col 43}{space 1}    0.27{col 52}{space 3}0.784{col 60}{space 4}-.4345376{col 73}{space 3} .5752097
{txt}{space 6}not working  {c |}{col 20}{res}{space 2} .3992049{col 32}{space 2} .3427701{col 43}{space 1}    1.16{col 52}{space 3}0.245{col 60}{space 4}-.2749377{col 73}{space 3} 1.073348
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2} .0067428{col 32}{space 2} .3242506{col 43}{space 1}    0.02{col 52}{space 3}0.983{col 60}{space 4}-.6368756{col 73}{space 3} .6503611
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .2087058{col 32}{space 2}  .137419{col 43}{space 1}    1.52{col 52}{space 3}0.130{col 60}{space 4}-.0622207{col 73}{space 3} .4796322
{txt}{space 11}selfest {c |}{col 20}{res}{space 2}-.1069021{col 32}{space 2} .3192699{col 43}{space 1}   -0.33{col 52}{space 3}0.738{col 60}{space 4}-.7353505{col 73}{space 3} .5215462
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 2.864237{col 32}{space 2} 1.404573{col 43}{space 1}    2.04{col 52}{space 3}0.042{col 60}{space 4} .1018792{col 73}{space 3} 5.626595
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHwhite threat2 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest if treatment==0 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       403

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res}  405.77968
{txt}{col 1}Number of PSUs{col 19}= {res}      403
{txt}{col 49}Average RVI{col 67}= {res}    0.1319
{txt}{col 49}Largest FMI{col 67}= {res}    0.2374
{txt}{col 49}Complete DF{col 67}= {res}       402
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    111.15
{txt}{col 49}        avg{col 67}= {res}    279.64
{txt}{col 49}        max{col 67}= {res}    372.55
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  15{txt},{res}  384.1{txt}){col 67}= {res}      1.93
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0196

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           GHwhite{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat2 {c |}{col 20}{res}{space 2}  .092616{col 32}{space 2} .0993688{col 43}{space 1}    0.93{col 52}{space 3}0.352{col 60}{space 4}-.1029161{col 73}{space 3} .2881482
{txt}{space 12}female {c |}{col 20}{res}{space 2} .3156789{col 32}{space 2} .1331434{col 43}{space 1}    2.37{col 52}{space 3}0.018{col 60}{space 4} .0538551{col 73}{space 3} .5775028
{txt}{space 15}Age {c |}{col 20}{res}{space 2}-.0137559{col 32}{space 2} .0071896{col 43}{space 1}   -1.91{col 52}{space 3}0.057{col 60}{space 4}-.0279025{col 73}{space 3} .0003906
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0241632{col 32}{space 2} .0446662{col 43}{space 1}   -0.54{col 52}{space 3}0.589{col 60}{space 4}-.1120581{col 73}{space 3} .0637318
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2}-.0393206{col 32}{space 2} .1674601{col 43}{space 1}   -0.23{col 52}{space 3}0.815{col 60}{space 4}-.3687781{col 73}{space 3}  .290137
{txt}{space 15}C2  {c |}{col 20}{res}{space 2} .0515016{col 32}{space 2} .2512841{col 43}{space 1}    0.20{col 52}{space 3}0.838{col 60}{space 4}-.4429655{col 73}{space 3} .5459688
{txt}{space 15}DE  {c |}{col 20}{res}{space 2} .0810498{col 32}{space 2} .2324942{col 43}{space 1}    0.35{col 52}{space 3}0.728{col 60}{space 4}-.3764087{col 73}{space 3} .5385083
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2}-.1730509{col 32}{space 2} .1714915{col 43}{space 1}   -1.01{col 52}{space 3}0.314{col 60}{space 4}-.5102635{col 73}{space 3} .1641616
{txt}full time student  {c |}{col 20}{res}{space 2} .5482863{col 32}{space 2} .4029132{col 43}{space 1}    1.36{col 52}{space 3}0.175{col 60}{space 4}-.2456992{col 73}{space 3} 1.342272
{txt}{space 10}retired  {c |}{col 20}{res}{space 2}  .217642{col 32}{space 2} .2276237{col 43}{space 1}    0.96{col 52}{space 3}0.340{col 60}{space 4}-.2303418{col 73}{space 3} .6656258
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2} .0338433{col 32}{space 2} .2451455{col 43}{space 1}    0.14{col 52}{space 3}0.890{col 60}{space 4}-.4493486{col 73}{space 3} .5170351
{txt}{space 6}not working  {c |}{col 20}{res}{space 2} .3937807{col 32}{space 2} .3498745{col 43}{space 1}    1.13{col 52}{space 3}0.261{col 60}{space 4}-.2943195{col 73}{space 3} 1.081881
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2} .0036576{col 32}{space 2} .3468824{col 43}{space 1}    0.01{col 52}{space 3}0.992{col 60}{space 4}-.6837027{col 73}{space 3} .6910179
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .2544514{col 32}{space 2}  .137254{col 43}{space 1}    1.85{col 52}{space 3}0.065{col 60}{space 4}-.0164698{col 73}{space 3} .5253725
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .0718902{col 32}{space 2} .2875183{col 43}{space 1}    0.25{col 52}{space 3}0.803{col 60}{space 4}-.4946494{col 73}{space 3} .6384298
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 2.276701{col 32}{space 2} 1.247631{col 43}{space 1}    1.82{col 52}{space 3}0.069{col 60}{space 4}-.1791183{col 73}{space 3}  4.73252
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHwhite threat3 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest if treatment==0 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       402

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 404.645592
{txt}{col 1}Number of PSUs{col 19}= {res}      402
{txt}{col 49}Average RVI{col 67}= {res}    0.1336
{txt}{col 49}Largest FMI{col 67}= {res}    0.2059
{txt}{col 49}Complete DF{col 67}= {res}       401
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    133.61
{txt}{col 49}        avg{col 67}= {res}    276.73
{txt}{col 49}        max{col 67}= {res}    368.34
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  15{txt},{res}  383.0{txt}){col 67}= {res}      2.30
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0038

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           GHwhite{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat3 {c |}{col 20}{res}{space 2} .2233685{col 32}{space 2} .0885222{col 43}{space 1}    2.52{col 52}{space 3}0.012{col 60}{space 4} .0491392{col 73}{space 3} .3975977
{txt}{space 12}female {c |}{col 20}{res}{space 2} .2591173{col 32}{space 2} .1342999{col 43}{space 1}    1.93{col 52}{space 3}0.054{col 60}{space 4} -.005019{col 73}{space 3} .5232536
{txt}{space 15}Age {c |}{col 20}{res}{space 2}-.0142497{col 32}{space 2} .0072103{col 43}{space 1}   -1.98{col 52}{space 3}0.049{col 60}{space 4}-.0284356{col 73}{space 3}-.0000638
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0171099{col 32}{space 2} .0450269{col 43}{space 1}   -0.38{col 52}{space 3}0.704{col 60}{space 4}-.1057093{col 73}{space 3} .0714895
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2} -.044372{col 32}{space 2} .1657505{col 43}{space 1}   -0.27{col 52}{space 3}0.789{col 60}{space 4}-.3704615{col 73}{space 3} .2817175
{txt}{space 15}C2  {c |}{col 20}{res}{space 2}-.0392437{col 32}{space 2} .2330577{col 43}{space 1}   -0.17{col 52}{space 3}0.866{col 60}{space 4}-.4979624{col 73}{space 3} .4194749
{txt}{space 15}DE  {c |}{col 20}{res}{space 2} .0727778{col 32}{space 2} .2382756{col 43}{space 1}    0.31{col 52}{space 3}0.760{col 60}{space 4}-.3960849{col 73}{space 3} .5416405
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2}-.0903399{col 32}{space 2}  .170556{col 43}{space 1}   -0.53{col 52}{space 3}0.597{col 60}{space 4}-.4257255{col 73}{space 3} .2450457
{txt}full time student  {c |}{col 20}{res}{space 2} .6485419{col 32}{space 2} .3920152{col 43}{space 1}    1.65{col 52}{space 3}0.100{col 60}{space 4}-.1241514{col 73}{space 3} 1.421235
{txt}{space 10}retired  {c |}{col 20}{res}{space 2} .2431601{col 32}{space 2} .2307715{col 43}{space 1}    1.05{col 52}{space 3}0.293{col 60}{space 4}-.2110482{col 73}{space 3} .6973684
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2} .1654547{col 32}{space 2}   .22726{col 43}{space 1}    0.73{col 52}{space 3}0.467{col 60}{space 4} -.282804{col 73}{space 3} .6137133
{txt}{space 6}not working  {c |}{col 20}{res}{space 2} .4832046{col 32}{space 2} .3482924{col 43}{space 1}    1.39{col 52}{space 3}0.166{col 60}{space 4}-.2018285{col 73}{space 3} 1.168238
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2} .1210777{col 32}{space 2} .3659625{col 43}{space 1}    0.33{col 52}{space 3}0.741{col 60}{space 4}-.6027516{col 73}{space 3}  .844907
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .2277729{col 32}{space 2} .1387265{col 43}{space 1}    1.64{col 52}{space 3}0.102{col 60}{space 4}-.0459015{col 73}{space 3} .5014473
{txt}{space 11}selfest {c |}{col 20}{res}{space 2}-.0378795{col 32}{space 2} .2827029{col 43}{space 1}   -0.13{col 52}{space 3}0.894{col 60}{space 4}-.5950484{col 73}{space 3} .5192894
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 1.778717{col 32}{space 2} 1.227281{col 43}{space 1}    1.45{col 52}{space 3}0.148{col 60}{space 4}-.6365097{col 73}{space 3} 4.193943
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHwhite threat4 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest if treatment==0 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       403

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 406.097308
{txt}{col 1}Number of PSUs{col 19}= {res}      403
{txt}{col 49}Average RVI{col 67}= {res}    0.1251
{txt}{col 49}Largest FMI{col 67}= {res}    0.1783
{txt}{col 49}Complete DF{col 67}= {res}       402
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    158.47
{txt}{col 49}        avg{col 67}= {res}    284.85
{txt}{col 49}        max{col 67}= {res}    366.13
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  15{txt},{res}  385.5{txt}){col 67}= {res}      2.22
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0055

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           GHwhite{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat4 {c |}{col 20}{res}{space 2}  .129962{col 32}{space 2}  .084405{col 43}{space 1}    1.54{col 52}{space 3}0.125{col 60}{space 4}-.0361657{col 73}{space 3} .2960897
{txt}{space 12}female {c |}{col 20}{res}{space 2} .3091734{col 32}{space 2} .1276961{col 43}{space 1}    2.42{col 52}{space 3}0.016{col 60}{space 4} .0580448{col 73}{space 3} .5603021
{txt}{space 15}Age {c |}{col 20}{res}{space 2}-.0136368{col 32}{space 2} .0072529{col 43}{space 1}   -1.88{col 52}{space 3}0.061{col 60}{space 4}-.0279081{col 73}{space 3} .0006345
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0247268{col 32}{space 2} .0441803{col 43}{space 1}   -0.56{col 52}{space 3}0.576{col 60}{space 4}-.1116345{col 73}{space 3} .0621808
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2}-.0597341{col 32}{space 2} .1664457{col 43}{space 1}   -0.36{col 52}{space 3}0.720{col 60}{space 4}-.3871472{col 73}{space 3}  .267679
{txt}{space 15}C2  {c |}{col 20}{res}{space 2} .0064124{col 32}{space 2} .2347114{col 43}{space 1}    0.03{col 52}{space 3}0.978{col 60}{space 4} -.455609{col 73}{space 3} .4684338
{txt}{space 15}DE  {c |}{col 20}{res}{space 2} .0912699{col 32}{space 2} .2363293{col 43}{space 1}    0.39{col 52}{space 3}0.700{col 60}{space 4}-.3737277{col 73}{space 3} .5562676
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2}-.1630738{col 32}{space 2} .1666235{col 43}{space 1}   -0.98{col 52}{space 3}0.328{col 60}{space 4} -.490733{col 73}{space 3} .1645854
{txt}full time student  {c |}{col 20}{res}{space 2} .6868669{col 32}{space 2} .3880024{col 43}{space 1}    1.77{col 52}{space 3}0.078{col 60}{space 4}-.0780002{col 73}{space 3} 1.451734
{txt}{space 10}retired  {c |}{col 20}{res}{space 2} .2019425{col 32}{space 2} .2286477{col 43}{space 1}    0.88{col 52}{space 3}0.378{col 60}{space 4}-.2481118{col 73}{space 3} .6519968
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2} .1029821{col 32}{space 2} .2487099{col 43}{space 1}    0.41{col 52}{space 3}0.679{col 60}{space 4}-.3870819{col 73}{space 3} .5930462
{txt}{space 6}not working  {c |}{col 20}{res}{space 2} .4357534{col 32}{space 2} .3464016{col 43}{space 1}    1.26{col 52}{space 3}0.209{col 60}{space 4}-.2455196{col 73}{space 3} 1.117027
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2}-.1136702{col 32}{space 2} .3327734{col 43}{space 1}   -0.34{col 52}{space 3}0.733{col 60}{space 4}-.7709132{col 73}{space 3} .5435728
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .2427233{col 32}{space 2}  .137269{col 43}{space 1}    1.77{col 52}{space 3}0.079{col 60}{space 4}-.0281554{col 73}{space 3} .5136021
{txt}{space 11}selfest {c |}{col 20}{res}{space 2}-.0382105{col 32}{space 2} .2875602{col 43}{space 1}   -0.13{col 52}{space 3}0.894{col 60}{space 4}-.6050013{col 73}{space 3} .5285803
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 2.327478{col 32}{space 2} 1.142324{col 43}{space 1}    2.04{col 52}{space 3}0.042{col 60}{space 4} .0807281{col 73}{space 3} 4.574229
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHwhite threat5 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest if treatment==0 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       405

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 407.959097
{txt}{col 1}Number of PSUs{col 19}= {res}      405
{txt}{col 49}Average RVI{col 67}= {res}    0.1404
{txt}{col 49}Largest FMI{col 67}= {res}    0.2507
{txt}{col 49}Complete DF{col 67}= {res}       404
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    103.30
{txt}{col 49}        avg{col 67}= {res}    282.14
{txt}{col 49}        max{col 67}= {res}    372.05
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  15{txt},{res}  383.9{txt}){col 67}= {res}      2.16
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0072

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           GHwhite{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat5 {c |}{col 20}{res}{space 2} .1614653{col 32}{space 2} .0998828{col 43}{space 1}    1.62{col 52}{space 3}0.107{col 60}{space 4}-.0351518{col 73}{space 3} .3580824
{txt}{space 12}female {c |}{col 20}{res}{space 2} .3076987{col 32}{space 2} .1305978{col 43}{space 1}    2.36{col 52}{space 3}0.019{col 60}{space 4} .0508825{col 73}{space 3} .5645149
{txt}{space 15}Age {c |}{col 20}{res}{space 2}-.0146303{col 32}{space 2} .0071929{col 43}{space 1}   -2.03{col 52}{space 3}0.043{col 60}{space 4}-.0287822{col 73}{space 3}-.0004784
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0249922{col 32}{space 2} .0439803{col 43}{space 1}   -0.57{col 52}{space 3}0.570{col 60}{space 4} -.111524{col 73}{space 3} .0615397
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2}-.0280176{col 32}{space 2} .1643871{col 43}{space 1}   -0.17{col 52}{space 3}0.865{col 60}{space 4}-.3514328{col 73}{space 3} .2953976
{txt}{space 15}C2  {c |}{col 20}{res}{space 2} .0455966{col 32}{space 2} .2477102{col 43}{space 1}    0.18{col 52}{space 3}0.854{col 60}{space 4}-.4418198{col 73}{space 3} .5330131
{txt}{space 15}DE  {c |}{col 20}{res}{space 2} .0360022{col 32}{space 2} .2308621{col 43}{space 1}    0.16{col 52}{space 3}0.876{col 60}{space 4}-.4182939{col 73}{space 3} .4902982
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2}-.1574294{col 32}{space 2} .1715326{col 43}{space 1}   -0.92{col 52}{space 3}0.359{col 60}{space 4}-.4947244{col 73}{space 3} .1798656
{txt}full time student  {c |}{col 20}{res}{space 2} .5662546{col 32}{space 2} .4017557{col 43}{space 1}    1.41{col 52}{space 3}0.160{col 60}{space 4}-.2253419{col 73}{space 3} 1.357851
{txt}{space 10}retired  {c |}{col 20}{res}{space 2} .2678332{col 32}{space 2} .2292407{col 43}{space 1}    1.17{col 52}{space 3}0.244{col 60}{space 4} -.183281{col 73}{space 3} .7189475
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2} .0328737{col 32}{space 2} .2443172{col 43}{space 1}    0.13{col 52}{space 3}0.893{col 60}{space 4}-.4486134{col 73}{space 3} .5143608
{txt}{space 6}not working  {c |}{col 20}{res}{space 2} .3594179{col 32}{space 2} .3476442{col 43}{space 1}    1.03{col 52}{space 3}0.302{col 60}{space 4}-.3243267{col 73}{space 3} 1.043162
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2}-.0900299{col 32}{space 2} .3390525{col 43}{space 1}   -0.27{col 52}{space 3}0.791{col 60}{space 4}-.7624372{col 73}{space 3} .5823774
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2}  .263519{col 32}{space 2} .1360495{col 43}{space 1}    1.94{col 52}{space 3}0.054{col 60}{space 4}-.0049528{col 73}{space 3} .5319908
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .0852119{col 32}{space 2} .2838853{col 43}{space 1}    0.30{col 52}{space 3}0.764{col 60}{space 4}-.4738232{col 73}{space 3} .6442469
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 2.163569{col 32}{space 2}  1.20541{col 43}{space 1}    1.79{col 52}{space 3}0.074{col 60}{space 4}-.2088006{col 73}{space 3} 4.535938
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. 
. *********************************************************************
. * DISCUSSION IN THE PAPER OF SOME ESTIMATES IN FIGURE 1 IN TERMS OF THE IMPACT 
. * ON HOSTILITY OF ONE STANDARD DEVIATION (SD) INCREASE IN CULTURAL AND COLLECTIVE SAFETY THREAT:
. **      NOTE: Only calculated for decoupled threat4 (GHBlack, GHMus, GHEEur) and threat3 (GHMus) 
. *********************************************************************
. 
. * SD for threat4
. mi estimate: svy: mean threat4
{res}
{txt}Multiple-imputation estimates{col 35}Imputations{col 51}= {res}        10
{txt}Survey: Mean estimation{col 35}Number of obs{col 51}= {res}       866

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 35}Population size{col 51}={res} 868.881373
{txt}{col 1}Number of PSUs{col 19}= {res}      866
{txt}{col 35}Average RVI{col 51}= {res}    0.0000
{txt}{col 35}Largest FMI{col 51}= {res}    0.0000
{txt}{col 35}Complete DF{col 51}= {res}       865
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 35}DF:     min{col 51}= {res}    863.01
{txt}{col 35}        avg{col 51}= {res}    863.01
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 35}        max{col 51}= {res}    863.01

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 5}threat4 {c |}{col 14}{res}{space 2} 2.964239{col 26}{space 2}  .034628{col 37}{space 5} 2.896274{col 51}{space 3} 3.032204
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}
{res}{txt}
{com}. matrix b = e(b_mi)
{txt}
{com}. scalar m = b[1,1]
{txt}
{com}. gen threat4_v = (threat4 - m)^2 
{txt}(683 missing values generated)

{com}. mi estimate: svy: mean threat4_v
{res}
{txt}Multiple-imputation estimates{col 35}Imputations{col 51}= {res}        10
{txt}Survey: Mean estimation{col 35}Number of obs{col 51}= {res}       866

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 35}Population size{col 51}={res} 868.881373
{txt}{col 1}Number of PSUs{col 19}= {res}      866
{txt}{col 35}Average RVI{col 51}= {res}    0.0000
{txt}{col 35}Largest FMI{col 51}= {res}    0.0000
{txt}{col 35}Complete DF{col 51}= {res}       865
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 35}DF:     min{col 51}= {res}    863.01
{txt}{col 35}        avg{col 51}= {res}    863.01
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 35}        max{col 51}= {res}    863.01

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 3}threat4_v {c |}{col 14}{res}{space 2} .9571112{col 26}{space 2}  .038944{col 37}{space 5} .8806751{col 51}{space 3} 1.033547
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}
{res}{txt}
{com}. matrix b = e(b_mi)
{txt}
{com}. scalar threat4_sd2 = b[1,1]
{txt}
{com}. 
. * SD for GHMus
. mi estimate: svy: mean GHMus
{res}
{txt}Multiple-imputation estimates{col 35}Imputations{col 51}= {res}        10
{txt}Survey: Mean estimation{col 35}Number of obs{col 51}= {res}       723

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 35}Population size{col 51}={res} 719.942589
{txt}{col 1}Number of PSUs{col 19}= {res}      723
{txt}{col 35}Average RVI{col 51}= {res}    0.0537
{txt}{col 35}Largest FMI{col 51}= {res}    0.0516
{txt}{col 35}Complete DF{col 51}= {res}       722
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 35}DF:     min{col 51}= {res}    570.81
{txt}{col 35}        avg{col 51}= {res}    570.81
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 35}        max{col 51}= {res}    570.81

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 7}GHMus {c |}{col 14}{res}{space 2} 2.261997{col 26}{space 2} .0278112{col 37}{space 5} 2.207372{col 51}{space 3} 2.316621
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}
{res}{txt}
{com}. matrix b = e(b_mi)
{txt}
{com}. scalar m = b[1,1]
{txt}
{com}. gen GHMus_v = (GHMus - m)^2 
{txt}(2,439 missing values generated)

{com}. mi estimate: svy: mean GHMus_v
{res}
{txt}Multiple-imputation estimates{col 35}Imputations{col 51}= {res}        10
{txt}Survey: Mean estimation{col 35}Number of obs{col 51}= {res}       723

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 35}Population size{col 51}={res} 719.942589
{txt}{col 1}Number of PSUs{col 19}= {res}      723
{txt}{col 35}Average RVI{col 51}= {res}    0.0369
{txt}{col 35}Largest FMI{col 51}= {res}    0.0360
{txt}{col 35}Complete DF{col 51}= {res}       722
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 35}DF:     min{col 51}= {res}    632.42
{txt}{col 35}        avg{col 51}= {res}    632.42
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 35}        max{col 51}= {res}    632.42

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 5}GHMus_v {c |}{col 14}{res}{space 2} .4932212{col 26}{space 2} .0246024{col 37}{space 5}  .444909{col 51}{space 3} .5415334
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}
{res}{txt}
{com}. matrix b = e(b_mi)
{txt}
{com}. scalar GHMus_sd2 = b[1,1]
{txt}
{com}. 
. * Effect of threat4 on GHMus
. mi estimate: svy: reg GHMus threat4 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest if treatment==0 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       415

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 417.232018
{txt}{col 1}Number of PSUs{col 19}= {res}      415
{txt}{col 49}Average RVI{col 67}= {res}    0.1283
{txt}{col 49}Largest FMI{col 67}= {res}    0.2295
{txt}{col 49}Complete DF{col 67}= {res}       414
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    117.60
{txt}{col 49}        avg{col 67}= {res}    254.82
{txt}{col 49}        max{col 67}= {res}    392.13
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  15{txt},{res}  394.9{txt}){col 67}= {res}     15.14
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}             GHMus{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat4 {c |}{col 20}{res}{space 2} .3146162{col 32}{space 2}  .038333{col 43}{space 1}    8.21{col 52}{space 3}0.000{col 60}{space 4} .2388926{col 73}{space 3} .3903398
{txt}{space 12}female {c |}{col 20}{res}{space 2}-.0530766{col 32}{space 2} .0629516{col 43}{space 1}   -0.84{col 52}{space 3}0.400{col 60}{space 4}-.1770332{col 73}{space 3}   .07088
{txt}{space 15}Age {c |}{col 20}{res}{space 2}-.0042419{col 32}{space 2} .0031435{col 43}{space 1}   -1.35{col 52}{space 3}0.178{col 60}{space 4}-.0104245{col 73}{space 3} .0019408
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0401444{col 32}{space 2} .0194328{col 43}{space 1}   -2.07{col 52}{space 3}0.040{col 60}{space 4}-.0784408{col 73}{space 3} -.001848
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2}-.2027162{col 32}{space 2} .0765819{col 43}{space 1}   -2.65{col 52}{space 3}0.009{col 60}{space 4}-.3534169{col 73}{space 3}-.0520155
{txt}{space 15}C2  {c |}{col 20}{res}{space 2}-.0309224{col 32}{space 2} .0945707{col 43}{space 1}   -0.33{col 52}{space 3}0.744{col 60}{space 4}-.2170036{col 73}{space 3} .1551587
{txt}{space 15}DE  {c |}{col 20}{res}{space 2} -.113213{col 32}{space 2} .1054854{col 43}{space 1}   -1.07{col 52}{space 3}0.284{col 60}{space 4}-.3209821{col 73}{space 3} .0945562
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2}-.1114827{col 32}{space 2} .0932329{col 43}{space 1}   -1.20{col 52}{space 3}0.233{col 60}{space 4} -.294964{col 73}{space 3} .0719987
{txt}full time student  {c |}{col 20}{res}{space 2} .0528014{col 32}{space 2}  .211388{col 43}{space 1}    0.25{col 52}{space 3}0.803{col 60}{space 4}-.3636051{col 73}{space 3}  .469208
{txt}{space 10}retired  {c |}{col 20}{res}{space 2} .1122349{col 32}{space 2} .1018702{col 43}{space 1}    1.10{col 52}{space 3}0.271{col 60}{space 4}-.0882164{col 73}{space 3} .3126861
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2}-.0250634{col 32}{space 2} .1974797{col 43}{space 1}   -0.13{col 52}{space 3}0.899{col 60}{space 4}-.4140355{col 73}{space 3} .3639087
{txt}{space 6}not working  {c |}{col 20}{res}{space 2} -.039003{col 32}{space 2} .1353528{col 43}{space 1}   -0.29{col 52}{space 3}0.774{col 60}{space 4}-.3063377{col 73}{space 3} .2283318
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2}-.4094215{col 32}{space 2} .4857981{col 43}{space 1}   -0.84{col 52}{space 3}0.400{col 60}{space 4}-1.364516{col 73}{space 3} .5456731
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .1708874{col 32}{space 2} .0574315{col 43}{space 1}    2.98{col 52}{space 3}0.003{col 60}{space 4} .0574198{col 73}{space 3} .2843549
{txt}{space 11}selfest {c |}{col 20}{res}{space 2}  .309448{col 32}{space 2} .1295688{col 43}{space 1}    2.39{col 52}{space 3}0.019{col 60}{space 4} .0528574{col 73}{space 3} .5660387
{txt}{space 13}_cons {c |}{col 20}{res}{space 2}  2.26454{col 32}{space 2}  .660411{col 43}{space 1}    3.43{col 52}{space 3}0.001{col 60}{space 4} .9652765{col 73}{space 3} 3.563803
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. matrix beta = e(b_mi)
{txt}
{com}. display(sqrt(threat4_sd2)*beta[1,1])/sqrt(GHMus_sd2)
{res}.43826968
{txt}
{com}. ** Result: a one SD increase in cultural threat is predicted to produce a .43826968 SD increase in GHMus
. 
. * SD for GHEEur
. mi estimate: svy: mean GHEEur
{res}
{txt}Multiple-imputation estimates{col 35}Imputations{col 51}= {res}        10
{txt}Survey: Mean estimation{col 35}Number of obs{col 51}= {res}       710

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 35}Population size{col 51}={res} 711.703502
{txt}{col 1}Number of PSUs{col 19}= {res}      710
{txt}{col 35}Average RVI{col 51}= {res}    0.0691
{txt}{col 35}Largest FMI{col 51}= {res}    0.0657
{txt}{col 35}Complete DF{col 51}= {res}       709
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 35}DF:     min{col 51}= {res}    506.06
{txt}{col 35}        avg{col 51}= {res}    506.06
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 35}        max{col 51}= {res}    506.06

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 6}GHEEur {c |}{col 14}{res}{space 2} 2.167698{col 26}{space 2} .0260044{col 37}{space 5} 2.116608{col 51}{space 3} 2.218788
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}
{res}{txt}
{com}. matrix b = e(b_mi)
{txt}
{com}. scalar m = b[1,1]
{txt}
{com}. gen GHEEur_v = (GHEEur - m)^2 
{txt}(2,599 missing values generated)

{com}. mi estimate: svy: mean GHEEur_v
{res}
{txt}Multiple-imputation estimates{col 35}Imputations{col 51}= {res}        10
{txt}Survey: Mean estimation{col 35}Number of obs{col 51}= {res}       710

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 35}Population size{col 51}={res} 711.703502
{txt}{col 1}Number of PSUs{col 19}= {res}      710
{txt}{col 35}Average RVI{col 51}= {res}    0.1711
{txt}{col 35}Largest FMI{col 51}= {res}    0.1505
{txt}{col 35}Complete DF{col 51}= {res}       709
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 35}DF:     min{col 51}= {res}    248.32
{txt}{col 35}        avg{col 51}= {res}    248.32
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 35}        max{col 51}= {res}    248.32

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 4}GHEEur_v {c |}{col 14}{res}{space 2} .4053214{col 26}{space 2} .0260293{col 37}{space 5} .3540552{col 51}{space 3} .4565877
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}
{res}{txt}
{com}. matrix b = e(b_mi)
{txt}
{com}. scalar GHEEur_sd2 = b[1,1]
{txt}
{com}. 
. * Effect of threat4 on GHEEur
. mi estimate: svy: reg GHEEur threat4 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest if treatment==0 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       413

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 415.299458
{txt}{col 1}Number of PSUs{col 19}= {res}      413
{txt}{col 49}Average RVI{col 67}= {res}    0.1823
{txt}{col 49}Largest FMI{col 67}= {res}    0.3497
{txt}{col 49}Complete DF{col 67}= {res}       412
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}     62.74
{txt}{col 49}        avg{col 67}= {res}    200.55
{txt}{col 49}        max{col 67}= {res}    330.57
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  15{txt},{res}  379.0{txt}){col 67}= {res}     10.11
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}            GHEEur{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat4 {c |}{col 20}{res}{space 2} .1990892{col 32}{space 2} .0339983{col 43}{space 1}    5.86{col 52}{space 3}0.000{col 60}{space 4}   .13195{col 73}{space 3} .2662285
{txt}{space 12}female {c |}{col 20}{res}{space 2}-.0299521{col 32}{space 2} .0570515{col 43}{space 1}   -0.53{col 52}{space 3}0.600{col 60}{space 4}-.1424507{col 73}{space 3} .0825465
{txt}{space 15}Age {c |}{col 20}{res}{space 2}-.0038443{col 32}{space 2} .0029843{col 43}{space 1}   -1.29{col 52}{space 3}0.199{col 60}{space 4}-.0097151{col 73}{space 3} .0020265
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0563464{col 32}{space 2} .0177273{col 43}{space 1}   -3.18{col 52}{space 3}0.002{col 60}{space 4}-.0912986{col 73}{space 3}-.0213942
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2}-.0691977{col 32}{space 2} .0651102{col 43}{space 1}   -1.06{col 52}{space 3}0.289{col 60}{space 4}-.1973835{col 73}{space 3} .0589881
{txt}{space 15}C2  {c |}{col 20}{res}{space 2} .0473265{col 32}{space 2} .0951335{col 43}{space 1}    0.50{col 52}{space 3}0.619{col 60}{space 4}-.1399555{col 73}{space 3} .2346085
{txt}{space 15}DE  {c |}{col 20}{res}{space 2}-.0561687{col 32}{space 2} .0891877{col 43}{space 1}   -0.63{col 52}{space 3}0.529{col 60}{space 4}-.2317053{col 73}{space 3} .1193678
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2}-.1542425{col 32}{space 2} .0902415{col 43}{space 1}   -1.71{col 52}{space 3}0.089{col 60}{space 4}-.3325226{col 73}{space 3} .0240377
{txt}full time student  {c |}{col 20}{res}{space 2}-.1800214{col 32}{space 2} .2077169{col 43}{space 1}   -0.87{col 52}{space 3}0.389{col 60}{space 4}-.5947894{col 73}{space 3} .2347465
{txt}{space 10}retired  {c |}{col 20}{res}{space 2} .0700944{col 32}{space 2} .0938218{col 43}{space 1}    0.75{col 52}{space 3}0.456{col 60}{space 4}-.1144688{col 73}{space 3} .2546575
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2}-.0339528{col 32}{space 2} .2077417{col 43}{space 1}   -0.16{col 52}{space 3}0.870{col 60}{space 4}-.4428388{col 73}{space 3} .3749333
{txt}{space 6}not working  {c |}{col 20}{res}{space 2}-.0122726{col 32}{space 2}  .143619{col 43}{space 1}   -0.09{col 52}{space 3}0.932{col 60}{space 4}-.2961503{col 73}{space 3} .2716052
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2}-.4604082{col 32}{space 2} .1242327{col 43}{space 1}   -3.71{col 52}{space 3}0.000{col 60}{space 4}-.7063074{col 73}{space 3}-.2145089
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2}  .166752{col 32}{space 2} .0571401{col 43}{space 1}    2.92{col 52}{space 3}0.005{col 60}{space 4} .0525574{col 73}{space 3} .2809466
{txt}{space 11}selfest {c |}{col 20}{res}{space 2}  .235276{col 32}{space 2} .1174533{col 43}{space 1}    2.00{col 52}{space 3}0.047{col 60}{space 4} .0029449{col 73}{space 3}  .467607
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 2.801046{col 32}{space 2} .4624962{col 43}{space 1}    6.06{col 52}{space 3}0.000{col 60}{space 4} 1.888415{col 73}{space 3} 3.713678
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. matrix beta = e(b_mi)
{txt}
{com}. display(sqrt(threat4_sd2)*beta[1,1])/sqrt(GHEEur_sd2)
{res}.30593501
{txt}
{com}. ** Result: a one SD increase in cultural threat is predicted to produce a .30593501 SD increase in GHEEur
. 
. * SD for GHblack
. mi estimate: svy: mean GHblack
{res}
{txt}Multiple-imputation estimates{col 35}Imputations{col 51}= {res}        10
{txt}Survey: Mean estimation{col 35}Number of obs{col 51}= {res}       732

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 35}Population size{col 51}={res} 731.915439
{txt}{col 1}Number of PSUs{col 19}= {res}      732
{txt}{col 35}Average RVI{col 51}= {res}    0.1382
{txt}{col 35}Largest FMI{col 51}= {res}    0.1246
{txt}{col 35}Complete DF{col 51}= {res}       731
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 35}DF:     min{col 51}= {res}    312.59
{txt}{col 35}        avg{col 51}= {res}    312.59
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 35}        max{col 51}= {res}    312.59

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 5}GHblack {c |}{col 14}{res}{space 2} 2.139731{col 26}{space 2} .0255878{col 37}{space 5} 2.089385{col 51}{space 3} 2.190077
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}
{res}{txt}
{com}. matrix b = e(b_mi)
{txt}
{com}. scalar m = b[1,1]
{txt}
{com}. gen GHblack_v = (GHblack - m)^2 
{txt}(2,320 missing values generated)

{com}. mi estimate: svy: mean GHblack_v
{res}
{txt}Multiple-imputation estimates{col 35}Imputations{col 51}= {res}        10
{txt}Survey: Mean estimation{col 35}Number of obs{col 51}= {res}       732

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 35}Population size{col 51}={res} 731.915439
{txt}{col 1}Number of PSUs{col 19}= {res}      732
{txt}{col 35}Average RVI{col 51}= {res}    0.1550
{txt}{col 35}Largest FMI{col 51}= {res}    0.1380
{txt}{col 35}Complete DF{col 51}= {res}       731
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 35}DF:     min{col 51}= {res}    278.88
{txt}{col 35}        avg{col 51}= {res}    278.88
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 35}        max{col 51}= {res}    278.88

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 3}GHblack_v {c |}{col 14}{res}{space 2} .3797666{col 26}{space 2}  .023781{col 37}{space 5} .3329536{col 51}{space 3} .4265796
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}
{res}{txt}
{com}. matrix b = e(b_mi)
{txt}
{com}. scalar GHblack_sd2 = b[1,1]
{txt}
{com}. 
. * Effect of threat4 on GHBlack
. mi estimate: svy: reg GHblack threat4 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest if treatment==0 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       418

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res}  419.70676
{txt}{col 1}Number of PSUs{col 19}= {res}      418
{txt}{col 49}Average RVI{col 67}= {res}    0.1268
{txt}{col 49}Largest FMI{col 67}= {res}    0.2921
{txt}{col 49}Complete DF{col 67}= {res}       417
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}     83.50
{txt}{col 49}        avg{col 67}= {res}    244.60
{txt}{col 49}        max{col 67}= {res}    387.42
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  15{txt},{res}  398.8{txt}){col 67}= {res}     12.43
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           GHblack{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat4 {c |}{col 20}{res}{space 2} .2024612{col 32}{space 2} .0323143{col 43}{space 1}    6.27{col 52}{space 3}0.000{col 60}{space 4} .1387191{col 73}{space 3} .2662033
{txt}{space 12}female {c |}{col 20}{res}{space 2}-.0925422{col 32}{space 2} .0534416{col 43}{space 1}   -1.73{col 52}{space 3}0.084{col 60}{space 4}-.1976886{col 73}{space 3} .0126042
{txt}{space 15}Age {c |}{col 20}{res}{space 2}-.0036351{col 32}{space 2} .0031677{col 43}{space 1}   -1.15{col 52}{space 3}0.253{col 60}{space 4}-.0098848{col 73}{space 3} .0026145
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0087287{col 32}{space 2} .0184394{col 43}{space 1}   -0.47{col 52}{space 3}0.637{col 60}{space 4}-.0454006{col 73}{space 3} .0279433
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2} .0026175{col 32}{space 2} .0672408{col 43}{space 1}    0.04{col 52}{space 3}0.969{col 60}{space 4}-.1297188{col 73}{space 3} .1349538
{txt}{space 15}C2  {c |}{col 20}{res}{space 2} .0057141{col 32}{space 2} .0892947{col 43}{space 1}    0.06{col 52}{space 3}0.949{col 60}{space 4}-.1698689{col 73}{space 3}  .181297
{txt}{space 15}DE  {c |}{col 20}{res}{space 2}-.0489362{col 32}{space 2} .0890625{col 43}{space 1}   -0.55{col 52}{space 3}0.583{col 60}{space 4}-.2247061{col 73}{space 3} .1268338
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2}-.1228002{col 32}{space 2} .0839015{col 43}{space 1}   -1.46{col 52}{space 3}0.144{col 60}{space 4}-.2878263{col 73}{space 3} .0422259
{txt}full time student  {c |}{col 20}{res}{space 2}-.1003928{col 32}{space 2} .1419922{col 43}{space 1}   -0.71{col 52}{space 3}0.480{col 60}{space 4}-.3797846{col 73}{space 3} .1789991
{txt}{space 10}retired  {c |}{col 20}{res}{space 2} .1168227{col 32}{space 2} .0941578{col 43}{space 1}    1.24{col 52}{space 3}0.216{col 60}{space 4}-.0685073{col 73}{space 3} .3021528
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2} .1424748{col 32}{space 2} .1954575{col 43}{space 1}    0.73{col 52}{space 3}0.467{col 60}{space 4}-.2420719{col 73}{space 3} .5270215
{txt}{space 6}not working  {c |}{col 20}{res}{space 2}-.0132786{col 32}{space 2} .1329761{col 43}{space 1}   -0.10{col 52}{space 3}0.921{col 60}{space 4}-.2757053{col 73}{space 3} .2491481
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2}-.4725976{col 32}{space 2} .2883647{col 43}{space 1}   -1.64{col 52}{space 3}0.102{col 60}{space 4}-1.039553{col 73}{space 3}  .094358
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .2946309{col 32}{space 2} .0536194{col 43}{space 1}    5.49{col 52}{space 3}0.000{col 60}{space 4} .1888054{col 73}{space 3} .4004563
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .2420784{col 32}{space 2} .1185687{col 43}{space 1}    2.04{col 52}{space 3}0.043{col 60}{space 4} .0079063{col 73}{space 3} .4762505
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 1.626383{col 32}{space 2} .5156185{col 43}{space 1}    3.15{col 52}{space 3}0.002{col 60}{space 4} .6071051{col 73}{space 3} 2.645662
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. matrix beta = e(b_mi)
{txt}
{com}. display(sqrt(threat4_sd2)*beta[1,1])/sqrt(GHblack_sd2)
{res}.32141382
{txt}
{com}. ** Result: a one SD increase in cultural threat is predicted to produce a .32141382 SD increase in GHBlack
. 
. * SD for threat3
. mi estimate: svy: mean threat3
{res}
{txt}Multiple-imputation estimates{col 35}Imputations{col 51}= {res}        10
{txt}Survey: Mean estimation{col 35}Number of obs{col 51}= {res}       857

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 35}Population size{col 51}={res} 858.267164
{txt}{col 1}Number of PSUs{col 19}= {res}      857
{txt}{col 35}Average RVI{col 51}= {res}    0.0000
{txt}{col 35}Largest FMI{col 51}= {res}    0.0000
{txt}{col 35}Complete DF{col 51}= {res}       856
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 35}DF:     min{col 51}= {res}    854.01
{txt}{col 35}        avg{col 51}= {res}    854.01
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 35}        max{col 51}= {res}    854.01

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 5}threat3 {c |}{col 14}{res}{space 2} 2.754574{col 26}{space 2} .0325137{col 37}{space 5} 2.690758{col 51}{space 3}  2.81839
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}
{res}{txt}
{com}. matrix b = e(b_mi)
{txt}
{com}. scalar m = b[1,1]
{txt}
{com}. gen threat3_v = (threat3 - m)^2 
{txt}(772 missing values generated)

{com}. mi estimate: svy: mean threat3_v
{res}
{txt}Multiple-imputation estimates{col 35}Imputations{col 51}= {res}        10
{txt}Survey: Mean estimation{col 35}Number of obs{col 51}= {res}       857

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 35}Population size{col 51}={res} 858.267164
{txt}{col 1}Number of PSUs{col 19}= {res}      857
{txt}{col 35}Average RVI{col 51}= {res}    0.0000
{txt}{col 35}Largest FMI{col 51}= {res}    0.0000
{txt}{col 35}Complete DF{col 51}= {res}       856
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 35}DF:     min{col 51}= {res}    854.01
{txt}{col 35}        avg{col 51}= {res}    854.01
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 35}        max{col 51}= {res}    854.01

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 3}threat3_v {c |}{col 14}{res}{space 2} .8329531{col 26}{space 2} .0339172{col 37}{space 5} .7663823{col 51}{space 3} .8995239
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}
{res}{txt}
{com}. matrix b = e(b_mi)
{txt}
{com}. scalar threat3_sd2 = b[1,1]
{txt}
{com}. 
. * Effect of threat3 on GHMus
. mi estimate: svy: reg GHMus threat3 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest if treatment==0 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       414

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 416.439681
{txt}{col 1}Number of PSUs{col 19}= {res}      414
{txt}{col 49}Average RVI{col 67}= {res}    0.1113
{txt}{col 49}Largest FMI{col 67}= {res}    0.2290
{txt}{col 49}Complete DF{col 67}= {res}       413
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    117.84
{txt}{col 49}        avg{col 67}= {res}    283.35
{txt}{col 49}        max{col 67}= {res}    401.68
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  15{txt},{res}  397.5{txt}){col 67}= {res}      9.07
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}             GHMus{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat3 {c |}{col 20}{res}{space 2}  .171793{col 32}{space 2} .0431498{col 43}{space 1}    3.98{col 52}{space 3}0.000{col 60}{space 4} .0869158{col 73}{space 3} .2566701
{txt}{space 12}female {c |}{col 20}{res}{space 2}-.0929999{col 32}{space 2} .0714675{col 43}{space 1}   -1.30{col 52}{space 3}0.194{col 60}{space 4}-.2336531{col 73}{space 3} .0476533
{txt}{space 15}Age {c |}{col 20}{res}{space 2} -.003024{col 32}{space 2} .0032767{col 43}{space 1}   -0.92{col 52}{space 3}0.357{col 60}{space 4}-.0094691{col 73}{space 3}  .003421
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0577194{col 32}{space 2} .0220544{col 43}{space 1}   -2.62{col 52}{space 3}0.009{col 60}{space 4}-.1011519{col 73}{space 3}-.0142868
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2} -.134558{col 32}{space 2} .0803328{col 43}{space 1}   -1.68{col 52}{space 3}0.095{col 60}{space 4}-.2925837{col 73}{space 3} .0234678
{txt}{space 15}C2  {c |}{col 20}{res}{space 2}-.0546238{col 32}{space 2} .1076158{col 43}{space 1}   -0.51{col 52}{space 3}0.612{col 60}{space 4}-.2663021{col 73}{space 3} .1570544
{txt}{space 15}DE  {c |}{col 20}{res}{space 2}-.0898679{col 32}{space 2} .1111136{col 43}{space 1}   -0.81{col 52}{space 3}0.419{col 60}{space 4}-.3086248{col 73}{space 3} .1288891
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2}-.1196248{col 32}{space 2} .1005632{col 43}{space 1}   -1.19{col 52}{space 3}0.235{col 60}{space 4}-.3175052{col 73}{space 3} .0782556
{txt}full time student  {c |}{col 20}{res}{space 2}-.0903269{col 32}{space 2} .2127335{col 43}{space 1}   -0.42{col 52}{space 3}0.672{col 60}{space 4}-.5093572{col 73}{space 3} .3287035
{txt}{space 10}retired  {c |}{col 20}{res}{space 2} .0988047{col 32}{space 2} .1089974{col 43}{space 1}    0.91{col 52}{space 3}0.365{col 60}{space 4}-.1156291{col 73}{space 3} .3132385
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2}-.0192194{col 32}{space 2} .2166407{col 43}{space 1}   -0.09{col 52}{space 3}0.929{col 60}{space 4}-.4457067{col 73}{space 3} .4072679
{txt}{space 6}not working  {c |}{col 20}{res}{space 2}-.0081336{col 32}{space 2} .1356364{col 43}{space 1}   -0.06{col 52}{space 3}0.952{col 60}{space 4}  -.27608{col 73}{space 3} .2598128
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2} .2282071{col 32}{space 2} .6422684{col 43}{space 1}    0.36{col 52}{space 3}0.723{col 60}{space 4} -1.03442{col 73}{space 3} 1.490835
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .2203915{col 32}{space 2} .0594995{col 43}{space 1}    3.70{col 52}{space 3}0.000{col 60}{space 4} .1031169{col 73}{space 3} .3376662
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .4236901{col 32}{space 2} .1350903{col 43}{space 1}    3.14{col 52}{space 3}0.002{col 60}{space 4} .1561708{col 73}{space 3} .6912094
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 2.212135{col 32}{space 2} .8326451{col 43}{space 1}    2.66{col 52}{space 3}0.008{col 60}{space 4} .5741339{col 73}{space 3} 3.850136
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. matrix beta = e(b_mi)
{txt}
{com}. display(sqrt(threat3_sd2)*beta[1,1])/sqrt(GHMus_sd2)
{res}.22325173
{txt}
{com}. ** Result: a one SD increase in collective safety threat is predicted to produce a .22325173 SD increase in GHMus
. 
. drop threat4_v-threat3_v
{txt}
{com}. 
. 
. *********************************************************************
. * FIGURE A.1B IN THE APPENDIX:
. *       Difference in Unstandardized OLS Coefficient Estimates and 95% Confidence Intervals 
. *       of the Impact of Coupled (C) and Decoupled (D) Threats on Group Hostility, 2011; 
. *       Threats Entered Individually
. *********************************************************************
. 
. * NOTE: The estimates and confidence intervals shown in FIGURE A.1B are those for the c.threat[]##treatment interaction effects 
. 
. mi estimate: svy: reg GHblack c.threat1##treatment female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       646

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 647.427455
{txt}{col 1}Number of PSUs{col 19}= {res}      646
{txt}{col 49}Average RVI{col 67}= {res}    0.1195
{txt}{col 49}Largest FMI{col 67}= {res}    0.2750
{txt}{col 49}Complete DF{col 67}= {res}       645
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    101.94
{txt}{col 49}        avg{col 67}= {res}    394.70
{txt}{col 49}        max{col 67}= {res}    627.23
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  17{txt},{res}  615.2{txt}){col 67}= {res}     15.96
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}                GHblack{col 25}{c |}      Coef.{col 37}   Std. Err.{col 49}      t{col 57}   P>|t|{col 65}     [95% Con{col 78}f. Interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 16}threat1 {c |}{col 25}{res}{space 2} .1311219{col 37}{space 2} .0361539{col 48}{space 1}    3.63{col 57}{space 3}0.000{col 65}{space 4} .0601009{col 78}{space 3}  .202143
{txt}{space 23} {c |}
{space 14}treatment {c |}
received coupled items  {c |}{col 25}{res}{space 2}-.2824498{col 37}{space 2}  .123062{col 48}{space 1}   -2.30{col 57}{space 3}0.022{col 65}{space 4}-.5241569{col 78}{space 3}-.0407427
{txt}{space 23} {c |}
{space 4}treatment#c.threat1 {c |}
received coupled items  {c |}{col 25}{res}{space 2} .1669269{col 37}{space 2} .0531802{col 48}{space 1}    3.14{col 57}{space 3}0.002{col 65}{space 4} .0624911{col 78}{space 3} .2713628
{txt}{space 23} {c |}
{space 17}female {c |}{col 25}{res}{space 2}-.0724484{col 37}{space 2} .0457324{col 48}{space 1}   -1.58{col 57}{space 3}0.114{col 65}{space 4}-.1623551{col 78}{space 3} .0174582
{txt}{space 20}Age {c |}{col 25}{res}{space 2} -.001313{col 37}{space 2} .0024733{col 48}{space 1}   -0.53{col 57}{space 3}0.596{col 65}{space 4}-.0061889{col 78}{space 3}  .003563
{txt}{space 16}edu_age {c |}{col 25}{res}{space 2}-.0272374{col 37}{space 2} .0148385{col 48}{space 1}   -1.84{col 57}{space 3}0.069{col 65}{space 4}-.0566697{col 78}{space 3}  .002195
{txt}{space 23} {c |}
{space 12}SocialGrade {c |}
{space 20}C1  {c |}{col 25}{res}{space 2} .0141423{col 37}{space 2} .0536741{col 48}{space 1}    0.26{col 57}{space 3}0.792{col 65}{space 4}-.0913504{col 78}{space 3} .1196351
{txt}{space 20}C2  {c |}{col 25}{res}{space 2}-.0704386{col 37}{space 2} .0889451{col 48}{space 1}   -0.79{col 57}{space 3}0.429{col 65}{space 4}-.2451279{col 78}{space 3} .1042507
{txt}{space 20}DE  {c |}{col 25}{res}{space 2}-.1013589{col 37}{space 2} .0722453{col 48}{space 1}   -1.40{col 57}{space 3}0.163{col 65}{space 4}-.2441494{col 78}{space 3} .0414316
{txt}{space 23} {c |}
{space 12}work_status {c |}
{space 5}working part time  {c |}{col 25}{res}{space 2}-.0754116{col 37}{space 2} .0662821{col 48}{space 1}   -1.14{col 57}{space 3}0.256{col 65}{space 4}-.2056237{col 78}{space 3} .0548005
{txt}{space 5}full time student  {c |}{col 25}{res}{space 2}  -.17925{col 37}{space 2} .1693291{col 48}{space 1}   -1.06{col 57}{space 3}0.290{col 65}{space 4}-.5119796{col 78}{space 3} .1534796
{txt}{space 15}retired  {c |}{col 25}{res}{space 2} .1316255{col 37}{space 2}  .072759{col 48}{space 1}    1.81{col 57}{space 3}0.071{col 65}{space 4}-.0113856{col 78}{space 3} .2746365
{txt}{space 12}unemployed  {c |}{col 25}{res}{space 2} .0339244{col 37}{space 2} .1391671{col 48}{space 1}    0.24{col 57}{space 3}0.808{col 65}{space 4}-.2394624{col 78}{space 3} .3073111
{txt}{space 11}not working  {c |}{col 25}{res}{space 2} .0252933{col 37}{space 2} .0978482{col 48}{space 1}    0.26{col 57}{space 3}0.796{col 65}{space 4}-.1672325{col 78}{space 3} .2178191
{txt}{space 23} {c |}
{space 17}UKborn {c |}{col 25}{res}{space 2} .0873323{col 37}{space 2} .2253495{col 48}{space 1}    0.39{col 57}{space 3}0.698{col 65}{space 4}-.3551985{col 78}{space 3} .5298631
{txt}{space 13}authvalues {c |}{col 25}{res}{space 2} .2714368{col 37}{space 2} .0424739{col 48}{space 1}    6.39{col 57}{space 3}0.000{col 65}{space 4} .1876821{col 78}{space 3} .3551914
{txt}{space 16}selfest {c |}{col 25}{res}{space 2} .2084766{col 37}{space 2} .0954937{col 48}{space 1}    2.18{col 57}{space 3}0.030{col 65}{space 4} .0203457{col 78}{space 3} .3966075
{txt}{space 18}_cons {c |}{col 25}{res}{space 2} 1.636776{col 37}{space 2} .4237648{col 48}{space 1}    3.86{col 57}{space 3}0.000{col 65}{space 4} .8004038{col 78}{space 3} 2.473148
{txt}{hline 24}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHblack c.threat2##treatment female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       649

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 650.427455
{txt}{col 1}Number of PSUs{col 19}= {res}      649
{txt}{col 49}Average RVI{col 67}= {res}    0.1107
{txt}{col 49}Largest FMI{col 67}= {res}    0.2426
{txt}{col 49}Complete DF{col 67}= {res}       648
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    124.35
{txt}{col 49}        avg{col 67}= {res}    387.27
{txt}{col 49}        max{col 67}= {res}    633.41
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  17{txt},{res}  619.7{txt}){col 67}= {res}     11.97
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}                GHblack{col 25}{c |}      Coef.{col 37}   Std. Err.{col 49}      t{col 57}   P>|t|{col 65}     [95% Con{col 78}f. Interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 16}threat2 {c |}{col 25}{res}{space 2} .0645762{col 37}{space 2} .0427328{col 48}{space 1}    1.51{col 57}{space 3}0.132{col 65}{space 4}-.0194489{col 78}{space 3} .1486013
{txt}{space 23} {c |}
{space 14}treatment {c |}
received coupled items  {c |}{col 25}{res}{space 2}-.2363862{col 37}{space 2} .1672295{col 48}{space 1}   -1.41{col 57}{space 3}0.158{col 65}{space 4}-.5648702{col 78}{space 3} .0920978
{txt}{space 23} {c |}
{space 4}treatment#c.threat2 {c |}
received coupled items  {c |}{col 25}{res}{space 2} .1416107{col 37}{space 2}  .061695{col 48}{space 1}    2.30{col 57}{space 3}0.022{col 65}{space 4}  .020417{col 78}{space 3} .2628043
{txt}{space 23} {c |}
{space 17}female {c |}{col 25}{res}{space 2}-.0754901{col 37}{space 2} .0459212{col 48}{space 1}   -1.64{col 57}{space 3}0.101{col 65}{space 4}-.1657806{col 78}{space 3} .0148004
{txt}{space 20}Age {c |}{col 25}{res}{space 2}-.0011212{col 37}{space 2} .0026105{col 48}{space 1}   -0.43{col 57}{space 3}0.668{col 65}{space 4}-.0062633{col 78}{space 3} .0040209
{txt}{space 16}edu_age {c |}{col 25}{res}{space 2}-.0298978{col 37}{space 2} .0154922{col 48}{space 1}   -1.93{col 57}{space 3}0.056{col 65}{space 4}-.0605603{col 78}{space 3} .0007647
{txt}{space 23} {c |}
{space 12}SocialGrade {c |}
{space 20}C1  {c |}{col 25}{res}{space 2} .0057725{col 37}{space 2} .0545913{col 48}{space 1}    0.11{col 57}{space 3}0.916{col 65}{space 4}-.1015122{col 78}{space 3} .1130572
{txt}{space 20}C2  {c |}{col 25}{res}{space 2}-.0697184{col 37}{space 2} .0865609{col 48}{space 1}   -0.81{col 57}{space 3}0.421{col 65}{space 4}-.2397261{col 78}{space 3} .1002892
{txt}{space 20}DE  {c |}{col 25}{res}{space 2}-.0870847{col 37}{space 2} .0753932{col 48}{space 1}   -1.16{col 57}{space 3}0.250{col 65}{space 4}-.2359529{col 78}{space 3} .0617834
{txt}{space 23} {c |}
{space 12}work_status {c |}
{space 5}working part time  {c |}{col 25}{res}{space 2}-.1057339{col 37}{space 2} .0691962{col 48}{space 1}   -1.53{col 57}{space 3}0.127{col 65}{space 4}-.2416521{col 78}{space 3} .0301844
{txt}{space 5}full time student  {c |}{col 25}{res}{space 2}-.1672376{col 37}{space 2} .1424322{col 48}{space 1}   -1.17{col 57}{space 3}0.241{col 65}{space 4}-.4472823{col 78}{space 3} .1128072
{txt}{space 15}retired  {c |}{col 25}{res}{space 2} .1375898{col 37}{space 2} .0793008{col 48}{space 1}    1.74{col 57}{space 3}0.083{col 65}{space 4}-.0182554{col 78}{space 3}  .293435
{txt}{space 12}unemployed  {c |}{col 25}{res}{space 2} -.004651{col 37}{space 2} .1478478{col 48}{space 1}   -0.03{col 57}{space 3}0.975{col 65}{space 4}-.2950662{col 78}{space 3} .2857642
{txt}{space 11}not working  {c |}{col 25}{res}{space 2} .0346545{col 37}{space 2} .0981415{col 48}{space 1}    0.35{col 57}{space 3}0.724{col 65}{space 4}-.1584357{col 78}{space 3} .2277446
{txt}{space 23} {c |}
{space 17}UKborn {c |}{col 25}{res}{space 2} .1445005{col 37}{space 2}  .241976{col 48}{space 1}    0.60{col 57}{space 3}0.551{col 65}{space 4}-.3306718{col 78}{space 3} .6196728
{txt}{space 13}authvalues {c |}{col 25}{res}{space 2} .3042605{col 37}{space 2} .0431833{col 48}{space 1}    7.05{col 57}{space 3}0.000{col 65}{space 4} .2191425{col 78}{space 3} .3893785
{txt}{space 16}selfest {c |}{col 25}{res}{space 2}  .215938{col 37}{space 2} .0977629{col 48}{space 1}    2.21{col 57}{space 3}0.028{col 65}{space 4} .0233627{col 78}{space 3} .4085134
{txt}{space 18}_cons {c |}{col 25}{res}{space 2} 1.677012{col 37}{space 2} .4576768{col 48}{space 1}    3.66{col 57}{space 3}0.000{col 65}{space 4} .7747956{col 78}{space 3} 2.579227
{txt}{hline 24}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHblack c.threat3##treatment female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       650

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 651.427455
{txt}{col 1}Number of PSUs{col 19}= {res}      650
{txt}{col 49}Average RVI{col 67}= {res}    0.1082
{txt}{col 49}Largest FMI{col 67}= {res}    0.2586
{txt}{col 49}Complete DF{col 67}= {res}       649
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    112.57
{txt}{col 49}        avg{col 67}= {res}    401.51
{txt}{col 49}        max{col 67}= {res}    634.28
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  17{txt},{res}  622.6{txt}){col 67}= {res}     11.89
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}                GHblack{col 25}{c |}      Coef.{col 37}   Std. Err.{col 49}      t{col 57}   P>|t|{col 65}     [95% Con{col 78}f. Interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 16}threat3 {c |}{col 25}{res}{space 2} .1051439{col 37}{space 2} .0378558{col 48}{space 1}    2.78{col 57}{space 3}0.006{col 65}{space 4} .0307686{col 78}{space 3} .1795193
{txt}{space 23} {c |}
{space 14}treatment {c |}
received coupled items  {c |}{col 25}{res}{space 2}-.1452251{col 37}{space 2} .1554344{col 48}{space 1}   -0.93{col 57}{space 3}0.351{col 65}{space 4} -.450518{col 78}{space 3} .1600678
{txt}{space 23} {c |}
{space 4}treatment#c.threat3 {c |}
received coupled items  {c |}{col 25}{res}{space 2} .0963605{col 37}{space 2} .0564367{col 48}{space 1}    1.71{col 57}{space 3}0.088{col 65}{space 4}-.0144882{col 78}{space 3} .2072091
{txt}{space 23} {c |}
{space 17}female {c |}{col 25}{res}{space 2}-.0865574{col 37}{space 2} .0470832{col 48}{space 1}   -1.84{col 57}{space 3}0.067{col 65}{space 4}-.1791131{col 78}{space 3} .0059982
{txt}{space 20}Age {c |}{col 25}{res}{space 2}-.0012346{col 37}{space 2} .0025049{col 48}{space 1}   -0.49{col 57}{space 3}0.623{col 65}{space 4}-.0061709{col 78}{space 3} .0037017
{txt}{space 16}edu_age {c |}{col 25}{res}{space 2}-.0223517{col 37}{space 2} .0154258{col 48}{space 1}   -1.45{col 57}{space 3}0.150{col 65}{space 4}-.0529142{col 78}{space 3} .0082109
{txt}{space 23} {c |}
{space 12}SocialGrade {c |}
{space 20}C1  {c |}{col 25}{res}{space 2} .0308563{col 37}{space 2} .0551224{col 48}{space 1}    0.56{col 57}{space 3}0.576{col 65}{space 4}-.0774688{col 78}{space 3} .1391814
{txt}{space 20}C2  {c |}{col 25}{res}{space 2} -.052792{col 37}{space 2} .0878644{col 48}{space 1}   -0.60{col 57}{space 3}0.548{col 65}{space 4}-.2253573{col 78}{space 3} .1197734
{txt}{space 20}DE  {c |}{col 25}{res}{space 2}-.0838605{col 37}{space 2} .0764119{col 48}{space 1}   -1.10{col 57}{space 3}0.274{col 65}{space 4} -.234798{col 78}{space 3} .0670771
{txt}{space 23} {c |}
{space 12}work_status {c |}
{space 5}working part time  {c |}{col 25}{res}{space 2}-.0892986{col 37}{space 2} .0697827{col 48}{space 1}   -1.28{col 57}{space 3}0.201{col 65}{space 4}-.2263751{col 78}{space 3} .0477779
{txt}{space 5}full time student  {c |}{col 25}{res}{space 2}-.1963599{col 37}{space 2} .1544289{col 48}{space 1}   -1.27{col 57}{space 3}0.204{col 65}{space 4} -.499893{col 78}{space 3} .1071731
{txt}{space 15}retired  {c |}{col 25}{res}{space 2} .1132125{col 37}{space 2}  .075913{col 48}{space 1}    1.49{col 57}{space 3}0.137{col 65}{space 4}-.0359656{col 78}{space 3} .2623907
{txt}{space 12}unemployed  {c |}{col 25}{res}{space 2} .0097327{col 37}{space 2} .1463712{col 48}{space 1}    0.07{col 57}{space 3}0.947{col 65}{space 4}-.2777773{col 78}{space 3} .2972428
{txt}{space 11}not working  {c |}{col 25}{res}{space 2} .0461237{col 37}{space 2} .0972201{col 48}{space 1}    0.47{col 57}{space 3}0.636{col 65}{space 4}-.1451593{col 78}{space 3} .2374067
{txt}{space 23} {c |}
{space 17}UKborn {c |}{col 25}{res}{space 2} .1408152{col 37}{space 2} .2316154{col 48}{space 1}    0.61{col 57}{space 3}0.543{col 65}{space 4}-.3140104{col 78}{space 3} .5956409
{txt}{space 13}authvalues {c |}{col 25}{res}{space 2} .2900458{col 37}{space 2} .0444392{col 48}{space 1}    6.53{col 57}{space 3}0.000{col 65}{space 4} .2025091{col 78}{space 3} .3775825
{txt}{space 16}selfest {c |}{col 25}{res}{space 2} .2819273{col 37}{space 2} .0987393{col 48}{space 1}    2.86{col 57}{space 3}0.005{col 65}{space 4}  .087505{col 78}{space 3} .4763497
{txt}{space 18}_cons {c |}{col 25}{res}{space 2} 1.456213{col 37}{space 2} .4498353{col 48}{space 1}    3.24{col 57}{space 3}0.001{col 65}{space 4} .5690604{col 78}{space 3} 2.343365
{txt}{hline 24}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHblack c.threat4##treatment female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       648

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 649.422187
{txt}{col 1}Number of PSUs{col 19}= {res}      648
{txt}{col 49}Average RVI{col 67}= {res}    0.1168
{txt}{col 49}Largest FMI{col 67}= {res}    0.2810
{txt}{col 49}Complete DF{col 67}= {res}       647
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}     98.56
{txt}{col 49}        avg{col 67}= {res}    366.02
{txt}{col 49}        max{col 67}= {res}    631.59
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  17{txt},{res}  617.0{txt}){col 67}= {res}     14.35
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}                GHblack{col 25}{c |}      Coef.{col 37}   Std. Err.{col 49}      t{col 57}   P>|t|{col 65}     [95% Con{col 78}f. Interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 16}threat4 {c |}{col 25}{res}{space 2} .1876975{col 37}{space 2} .0318495{col 48}{space 1}    5.89{col 57}{space 3}0.000{col 65}{space 4} .1249302{col 78}{space 3} .2504648
{txt}{space 23} {c |}
{space 14}treatment {c |}
received coupled items  {c |}{col 25}{res}{space 2} .1486541{col 37}{space 2}  .132802{col 48}{space 1}    1.12{col 57}{space 3}0.264{col 65}{space 4}-.1124048{col 78}{space 3}  .409713
{txt}{space 23} {c |}
{space 4}treatment#c.threat4 {c |}
received coupled items  {c |}{col 25}{res}{space 2} -.017875{col 37}{space 2} .0454886{col 48}{space 1}   -0.39{col 57}{space 3}0.695{col 65}{space 4}-.1072923{col 78}{space 3} .0715423
{txt}{space 23} {c |}
{space 17}female {c |}{col 25}{res}{space 2}-.0756719{col 37}{space 2} .0470641{col 48}{space 1}   -1.61{col 57}{space 3}0.109{col 65}{space 4} -.168187{col 78}{space 3} .0168433
{txt}{space 20}Age {c |}{col 25}{res}{space 2}-.0009159{col 37}{space 2} .0024557{col 48}{space 1}   -0.37{col 57}{space 3}0.710{col 65}{space 4}-.0057561{col 78}{space 3} .0039243
{txt}{space 16}edu_age {c |}{col 25}{res}{space 2}-.0134839{col 37}{space 2}  .015376{col 48}{space 1}   -0.88{col 57}{space 3}0.383{col 65}{space 4}-.0439949{col 78}{space 3}  .017027
{txt}{space 23} {c |}
{space 12}SocialGrade {c |}
{space 20}C1  {c |}{col 25}{res}{space 2}  .010352{col 37}{space 2} .0547444{col 48}{space 1}    0.19{col 57}{space 3}0.850{col 65}{space 4}-.0972294{col 78}{space 3} .1179334
{txt}{space 20}C2  {c |}{col 25}{res}{space 2}-.0365755{col 37}{space 2} .0885176{col 48}{space 1}   -0.41{col 57}{space 3}0.680{col 65}{space 4}-.2104239{col 78}{space 3} .1372728
{txt}{space 20}DE  {c |}{col 25}{res}{space 2} -.070291{col 37}{space 2} .0767098{col 48}{space 1}   -0.92{col 57}{space 3}0.361{col 65}{space 4}-.2218041{col 78}{space 3} .0812222
{txt}{space 23} {c |}
{space 12}work_status {c |}
{space 5}working part time  {c |}{col 25}{res}{space 2}-.1184635{col 37}{space 2} .0669419{col 48}{space 1}   -1.77{col 57}{space 3}0.077{col 65}{space 4}-.2499648{col 78}{space 3} .0130377
{txt}{space 5}full time student  {c |}{col 25}{res}{space 2}-.1063697{col 37}{space 2} .1726479{col 48}{space 1}   -0.62{col 57}{space 3}0.538{col 65}{space 4}-.4455999{col 78}{space 3} .2328606
{txt}{space 15}retired  {c |}{col 25}{res}{space 2} .0929107{col 37}{space 2}  .074837{col 48}{space 1}    1.24{col 57}{space 3}0.215{col 65}{space 4}-.0541596{col 78}{space 3} .2399809
{txt}{space 12}unemployed  {c |}{col 25}{res}{space 2} .0400213{col 37}{space 2} .1401004{col 48}{space 1}    0.29{col 57}{space 3}0.775{col 65}{space 4}-.2351837{col 78}{space 3} .3152262
{txt}{space 11}not working  {c |}{col 25}{res}{space 2} .0451867{col 37}{space 2} .0997653{col 48}{space 1}    0.45{col 57}{space 3}0.651{col 65}{space 4}-.1510877{col 78}{space 3} .2414611
{txt}{space 23} {c |}
{space 17}UKborn {c |}{col 25}{res}{space 2}-.0251599{col 37}{space 2} .2476627{col 48}{space 1}   -0.10{col 57}{space 3}0.919{col 65}{space 4}-.5115018{col 78}{space 3} .4611821
{txt}{space 13}authvalues {c |}{col 25}{res}{space 2} .2790138{col 37}{space 2}  .044832{col 48}{space 1}    6.22{col 57}{space 3}0.000{col 65}{space 4} .1906235{col 78}{space 3} .3674041
{txt}{space 16}selfest {c |}{col 25}{res}{space 2} .2117532{col 37}{space 2} .0973227{col 48}{space 1}    2.18{col 57}{space 3}0.030{col 65}{space 4} .0201197{col 78}{space 3} .4033868
{txt}{space 18}_cons {c |}{col 25}{res}{space 2} 1.224582{col 37}{space 2} .4405287{col 48}{space 1}    2.78{col 57}{space 3}0.006{col 65}{space 4}  .355104{col 78}{space 3} 2.094059
{txt}{hline 24}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHblack c.threat5##treatment female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       650

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 651.672206
{txt}{col 1}Number of PSUs{col 19}= {res}      650
{txt}{col 49}Average RVI{col 67}= {res}    0.1140
{txt}{col 49}Largest FMI{col 67}= {res}    0.2481
{txt}{col 49}Complete DF{col 67}= {res}       649
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    120.12
{txt}{col 49}        avg{col 67}= {res}    391.36
{txt}{col 49}        max{col 67}= {res}    632.61
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  17{txt},{res}  619.4{txt}){col 67}= {res}     12.17
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}                GHblack{col 25}{c |}      Coef.{col 37}   Std. Err.{col 49}      t{col 57}   P>|t|{col 65}     [95% Con{col 78}f. Interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 16}threat5 {c |}{col 25}{res}{space 2} .0384456{col 37}{space 2} .0427291{col 48}{space 1}    0.90{col 57}{space 3}0.369{col 65}{space 4}-.0455775{col 78}{space 3} .1224686
{txt}{space 23} {c |}
{space 14}treatment {c |}
received coupled items  {c |}{col 25}{res}{space 2}-.3932862{col 37}{space 2} .1630161{col 48}{space 1}   -2.41{col 57}{space 3}0.016{col 65}{space 4}-.7135042{col 78}{space 3}-.0730681
{txt}{space 23} {c |}
{space 4}treatment#c.threat5 {c |}
received coupled items  {c |}{col 25}{res}{space 2} .1784173{col 37}{space 2} .0566422{col 48}{space 1}    3.15{col 57}{space 3}0.002{col 65}{space 4} .0671512{col 78}{space 3} .2896834
{txt}{space 23} {c |}
{space 17}female {c |}{col 25}{res}{space 2}-.0908387{col 37}{space 2} .0473268{col 48}{space 1}   -1.92{col 57}{space 3}0.056{col 65}{space 4}-.1838802{col 78}{space 3} .0022028
{txt}{space 20}Age {c |}{col 25}{res}{space 2} -.001021{col 37}{space 2}  .002497{col 48}{space 1}   -0.41{col 57}{space 3}0.683{col 65}{space 4} -.005943{col 78}{space 3} .0039011
{txt}{space 16}edu_age {c |}{col 25}{res}{space 2}-.0292556{col 37}{space 2} .0150798{col 48}{space 1}   -1.94{col 57}{space 3}0.055{col 65}{space 4}-.0591122{col 78}{space 3}  .000601
{txt}{space 23} {c |}
{space 12}SocialGrade {c |}
{space 20}C1  {c |}{col 25}{res}{space 2} .0290833{col 37}{space 2} .0554409{col 48}{space 1}    0.52{col 57}{space 3}0.600{col 65}{space 4}-.0798668{col 78}{space 3} .1380333
{txt}{space 20}C2  {c |}{col 25}{res}{space 2}-.0600519{col 37}{space 2} .0904982{col 48}{space 1}   -0.66{col 57}{space 3}0.507{col 65}{space 4}-.2377833{col 78}{space 3} .1176794
{txt}{space 20}DE  {c |}{col 25}{res}{space 2}-.0570047{col 37}{space 2} .0738557{col 48}{space 1}   -0.77{col 57}{space 3}0.441{col 65}{space 4}-.2029659{col 78}{space 3} .0889566
{txt}{space 23} {c |}
{space 12}work_status {c |}
{space 5}working part time  {c |}{col 25}{res}{space 2}-.1187172{col 37}{space 2} .0682927{col 48}{space 1}   -1.74{col 57}{space 3}0.083{col 65}{space 4}-.2528624{col 78}{space 3} .0154279
{txt}{space 5}full time student  {c |}{col 25}{res}{space 2}-.1981348{col 37}{space 2} .1681799{col 48}{space 1}   -1.18{col 57}{space 3}0.239{col 65}{space 4}-.5286093{col 78}{space 3} .1323397
{txt}{space 15}retired  {c |}{col 25}{res}{space 2} .1005983{col 37}{space 2} .0754626{col 48}{space 1}    1.33{col 57}{space 3}0.183{col 65}{space 4}-.0477184{col 78}{space 3} .2489151
{txt}{space 12}unemployed  {c |}{col 25}{res}{space 2}-.0099135{col 37}{space 2} .1430078{col 48}{space 1}   -0.07{col 57}{space 3}0.945{col 65}{space 4}-.2908248{col 78}{space 3} .2709978
{txt}{space 11}not working  {c |}{col 25}{res}{space 2} .0192604{col 37}{space 2} .0976792{col 48}{space 1}    0.20{col 57}{space 3}0.844{col 65}{space 4}-.1729196{col 78}{space 3} .2114403
{txt}{space 23} {c |}
{space 17}UKborn {c |}{col 25}{res}{space 2} .1312031{col 37}{space 2} .2352892{col 48}{space 1}    0.56{col 57}{space 3}0.577{col 65}{space 4}-.3308392{col 78}{space 3} .5932453
{txt}{space 13}authvalues {c |}{col 25}{res}{space 2} .2915387{col 37}{space 2} .0448477{col 48}{space 1}    6.50{col 57}{space 3}0.000{col 65}{space 4} .2031587{col 78}{space 3} .3799186
{txt}{space 16}selfest {c |}{col 25}{res}{space 2} .2651992{col 37}{space 2} .0969675{col 48}{space 1}    2.73{col 57}{space 3}0.007{col 65}{space 4} .0742107{col 78}{space 3} .4561876
{txt}{space 18}_cons {c |}{col 25}{res}{space 2}  1.77582{col 37}{space 2} .4380443{col 48}{space 1}    4.05{col 57}{space 3}0.000{col 65}{space 4}  .912712{col 78}{space 3} 2.638927
{txt}{hline 24}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. mi estimate: svy: reg GHMus c.threat1##treatment female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       641

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 642.731731
{txt}{col 1}Number of PSUs{col 19}= {res}      641
{txt}{col 49}Average RVI{col 67}= {res}    0.1010
{txt}{col 49}Largest FMI{col 67}= {res}    0.1879
{txt}{col 49}Complete DF{col 67}= {res}       640
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    179.41
{txt}{col 49}        avg{col 67}= {res}    425.55
{txt}{col 49}        max{col 67}= {res}    615.92
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  17{txt},{res}  615.5{txt}){col 67}= {res}     16.04
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}                  GHMus{col 25}{c |}      Coef.{col 37}   Std. Err.{col 49}      t{col 57}   P>|t|{col 65}     [95% Con{col 78}f. Interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 16}threat1 {c |}{col 25}{res}{space 2} .1607386{col 37}{space 2} .0445271{col 48}{space 1}    3.61{col 57}{space 3}0.000{col 65}{space 4} .0732094{col 78}{space 3} .2482679
{txt}{space 23} {c |}
{space 14}treatment {c |}
received coupled items  {c |}{col 25}{res}{space 2}-.2586142{col 37}{space 2} .1416837{col 48}{space 1}   -1.83{col 57}{space 3}0.069{col 65}{space 4}-.5371082{col 78}{space 3} .0198798
{txt}{space 23} {c |}
{space 4}treatment#c.threat1 {c |}
received coupled items  {c |}{col 25}{res}{space 2} .1585541{col 37}{space 2} .0580162{col 48}{space 1}    2.73{col 57}{space 3}0.007{col 65}{space 4} .0445662{col 78}{space 3}  .272542
{txt}{space 23} {c |}
{space 17}female {c |}{col 25}{res}{space 2}-.0452816{col 37}{space 2} .0539211{col 48}{space 1}   -0.84{col 57}{space 3}0.402{col 65}{space 4}-.1513441{col 78}{space 3} .0607809
{txt}{space 20}Age {c |}{col 25}{res}{space 2}-.0018883{col 37}{space 2} .0024343{col 48}{space 1}   -0.78{col 57}{space 3}0.438{col 65}{space 4}-.0066703{col 78}{space 3} .0028938
{txt}{space 16}edu_age {c |}{col 25}{res}{space 2}-.0554861{col 37}{space 2}  .017158{col 48}{space 1}   -3.23{col 57}{space 3}0.001{col 65}{space 4}-.0892349{col 78}{space 3}-.0217373
{txt}{space 23} {c |}
{space 12}SocialGrade {c |}
{space 20}C1  {c |}{col 25}{res}{space 2}-.0531101{col 37}{space 2} .0618763{col 48}{space 1}   -0.86{col 57}{space 3}0.391{col 65}{space 4}-.1746907{col 78}{space 3} .0684705
{txt}{space 20}C2  {c |}{col 25}{res}{space 2}-.0716547{col 37}{space 2} .0917545{col 48}{space 1}   -0.78{col 57}{space 3}0.435{col 65}{space 4} -.251877{col 78}{space 3} .1085675
{txt}{space 20}DE  {c |}{col 25}{res}{space 2} -.030086{col 37}{space 2} .0836938{col 48}{space 1}   -0.36{col 57}{space 3}0.719{col 65}{space 4}-.1947862{col 78}{space 3} .1346142
{txt}{space 23} {c |}
{space 12}work_status {c |}
{space 5}working part time  {c |}{col 25}{res}{space 2}-.0275162{col 37}{space 2}  .077951{col 48}{space 1}   -0.35{col 57}{space 3}0.724{col 65}{space 4}-.1807082{col 78}{space 3} .1256758
{txt}{space 5}full time student  {c |}{col 25}{res}{space 2}-.1034296{col 37}{space 2}  .165424{col 48}{space 1}   -0.63{col 57}{space 3}0.532{col 65}{space 4}-.4285782{col 78}{space 3} .2217189
{txt}{space 15}retired  {c |}{col 25}{res}{space 2} .1119259{col 37}{space 2} .0826247{col 48}{space 1}    1.35{col 57}{space 3}0.176{col 65}{space 4}-.0503777{col 78}{space 3} .2742296
{txt}{space 12}unemployed  {c |}{col 25}{res}{space 2} .0104082{col 37}{space 2} .1378869{col 48}{space 1}    0.08{col 57}{space 3}0.940{col 65}{space 4}-.2606038{col 78}{space 3} .2814203
{txt}{space 11}not working  {c |}{col 25}{res}{space 2}  .023505{col 37}{space 2} .1036665{col 48}{space 1}    0.23{col 57}{space 3}0.821{col 65}{space 4}-.1803913{col 78}{space 3} .2274013
{txt}{space 23} {c |}
{space 17}UKborn {c |}{col 25}{res}{space 2} .1410193{col 37}{space 2} .3337218{col 48}{space 1}    0.42{col 57}{space 3}0.673{col 65}{space 4}-.5143513{col 78}{space 3}   .79639
{txt}{space 13}authvalues {c |}{col 25}{res}{space 2} .2324997{col 37}{space 2}  .045762{col 48}{space 1}    5.08{col 57}{space 3}0.000{col 65}{space 4} .1424145{col 78}{space 3} .3225848
{txt}{space 16}selfest {c |}{col 25}{res}{space 2} .2884363{col 37}{space 2}  .102229{col 48}{space 1}    2.82{col 57}{space 3}0.005{col 65}{space 4} .0867104{col 78}{space 3} .4901622
{txt}{space 18}_cons {c |}{col 25}{res}{space 2} 2.237745{col 37}{space 2} .5265937{col 48}{space 1}    4.25{col 57}{space 3}0.000{col 65}{space 4} 1.203165{col 78}{space 3} 3.272326
{txt}{hline 24}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHMus c.threat2##treatment female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       644

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 645.731731
{txt}{col 1}Number of PSUs{col 19}= {res}      644
{txt}{col 49}Average RVI{col 67}= {res}    0.1035
{txt}{col 49}Largest FMI{col 67}= {res}    0.1811
{txt}{col 49}Complete DF{col 67}= {res}       643
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    188.90
{txt}{col 49}        avg{col 67}= {res}    424.73
{txt}{col 49}        max{col 67}= {res}    616.86
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  17{txt},{res}  616.3{txt}){col 67}= {res}     14.73
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}                  GHMus{col 25}{c |}      Coef.{col 37}   Std. Err.{col 49}      t{col 57}   P>|t|{col 65}     [95% Con{col 78}f. Interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 16}threat2 {c |}{col 25}{res}{space 2} .0979593{col 37}{space 2} .0492194{col 48}{space 1}    1.99{col 57}{space 3}0.048{col 65}{space 4} .0010203{col 78}{space 3} .1948983
{txt}{space 23} {c |}
{space 14}treatment {c |}
received coupled items  {c |}{col 25}{res}{space 2}-.3591563{col 37}{space 2} .1792124{col 48}{space 1}   -2.00{col 57}{space 3}0.046{col 65}{space 4}-.7113067{col 78}{space 3}-.0070059
{txt}{space 23} {c |}
{space 4}treatment#c.threat2 {c |}
received coupled items  {c |}{col 25}{res}{space 2} .1966202{col 37}{space 2} .0629001{col 48}{space 1}    3.13{col 57}{space 3}0.002{col 65}{space 4} .0730185{col 78}{space 3} .3202219
{txt}{space 23} {c |}
{space 17}female {c |}{col 25}{res}{space 2}-.0624224{col 37}{space 2} .0535627{col 48}{space 1}   -1.17{col 57}{space 3}0.245{col 65}{space 4}-.1677714{col 78}{space 3} .0429266
{txt}{space 20}Age {c |}{col 25}{res}{space 2}-.0022693{col 37}{space 2} .0025661{col 48}{space 1}   -0.88{col 57}{space 3}0.377{col 65}{space 4}-.0073098{col 78}{space 3} .0027712
{txt}{space 16}edu_age {c |}{col 25}{res}{space 2}-.0601955{col 37}{space 2}  .017281{col 48}{space 1}   -3.48{col 57}{space 3}0.001{col 65}{space 4}-.0941743{col 78}{space 3}-.0262167
{txt}{space 23} {c |}
{space 12}SocialGrade {c |}
{space 20}C1  {c |}{col 25}{res}{space 2}-.0534487{col 37}{space 2} .0643039{col 48}{space 1}   -0.83{col 57}{space 3}0.406{col 65}{space 4}-.1797804{col 78}{space 3} .0728831
{txt}{space 20}C2  {c |}{col 25}{res}{space 2}-.0671413{col 37}{space 2} .0867772{col 48}{space 1}   -0.77{col 57}{space 3}0.439{col 65}{space 4}-.2375965{col 78}{space 3} .1033138
{txt}{space 20}DE  {c |}{col 25}{res}{space 2}-.0096236{col 37}{space 2} .0825386{col 48}{space 1}   -0.12{col 57}{space 3}0.907{col 65}{space 4}-.1720039{col 78}{space 3} .1527567
{txt}{space 23} {c |}
{space 12}work_status {c |}
{space 5}working part time  {c |}{col 25}{res}{space 2}-.0689565{col 37}{space 2} .0816551{col 48}{space 1}   -0.84{col 57}{space 3}0.399{col 65}{space 4} -.229403{col 78}{space 3} .0914901
{txt}{space 5}full time student  {c |}{col 25}{res}{space 2}-.1124119{col 37}{space 2} .1445963{col 48}{space 1}   -0.78{col 57}{space 3}0.437{col 65}{space 4}-.3968064{col 78}{space 3} .1719826
{txt}{space 15}retired  {c |}{col 25}{res}{space 2} .1298686{col 37}{space 2} .0853303{col 48}{space 1}    1.52{col 57}{space 3}0.129{col 65}{space 4}-.0377517{col 78}{space 3} .2974889
{txt}{space 12}unemployed  {c |}{col 25}{res}{space 2}-.0499796{col 37}{space 2} .1407371{col 48}{space 1}   -0.36{col 57}{space 3}0.723{col 65}{space 4}-.3265863{col 78}{space 3} .2266271
{txt}{space 11}not working  {c |}{col 25}{res}{space 2} .0190811{col 37}{space 2} .1062348{col 48}{space 1}    0.18{col 57}{space 3}0.858{col 65}{space 4}-.1898592{col 78}{space 3} .2280213
{txt}{space 23} {c |}
{space 17}UKborn {c |}{col 25}{res}{space 2} .2158887{col 37}{space 2} .3336412{col 48}{space 1}    0.65{col 57}{space 3}0.518{col 65}{space 4}-.4393216{col 78}{space 3} .8710989
{txt}{space 13}authvalues {c |}{col 25}{res}{space 2} .2513202{col 37}{space 2} .0476243{col 48}{space 1}    5.28{col 57}{space 3}0.000{col 65}{space 4} .1576001{col 78}{space 3} .3450404
{txt}{space 16}selfest {c |}{col 25}{res}{space 2} .2904744{col 37}{space 2}  .103783{col 48}{space 1}    2.80{col 57}{space 3}0.006{col 65}{space 4} .0857518{col 78}{space 3}  .495197
{txt}{space 18}_cons {c |}{col 25}{res}{space 2} 2.338539{col 37}{space 2} .5462285{col 48}{space 1}    4.28{col 57}{space 3}0.000{col 65}{space 4}  1.26551{col 78}{space 3} 3.411569
{txt}{hline 24}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHMus c.threat3##treatment female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       645

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 646.731731
{txt}{col 1}Number of PSUs{col 19}= {res}      645
{txt}{col 49}Average RVI{col 67}= {res}    0.1033
{txt}{col 49}Largest FMI{col 67}= {res}    0.2076
{txt}{col 49}Complete DF{col 67}= {res}       644
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    156.41
{txt}{col 49}        avg{col 67}= {res}    412.10
{txt}{col 49}        max{col 67}= {res}    622.49
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  17{txt},{res}  618.1{txt}){col 67}= {res}     16.96
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}                  GHMus{col 25}{c |}      Coef.{col 37}   Std. Err.{col 49}      t{col 57}   P>|t|{col 65}     [95% Con{col 78}f. Interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 16}threat3 {c |}{col 25}{res}{space 2} .1750748{col 37}{space 2} .0413862{col 48}{space 1}    4.23{col 57}{space 3}0.000{col 65}{space 4} .0937186{col 78}{space 3}  .256431
{txt}{space 23} {c |}
{space 14}treatment {c |}
received coupled items  {c |}{col 25}{res}{space 2}-.2996633{col 37}{space 2} .1566339{col 48}{space 1}   -1.91{col 57}{space 3}0.056{col 65}{space 4}-.6076398{col 78}{space 3} .0083133
{txt}{space 23} {c |}
{space 4}treatment#c.threat3 {c |}
received coupled items  {c |}{col 25}{res}{space 2} .1685506{col 37}{space 2} .0561512{col 48}{space 1}    3.00{col 57}{space 3}0.003{col 65}{space 4} .0581708{col 78}{space 3} .2789304
{txt}{space 23} {c |}
{space 17}female {c |}{col 25}{res}{space 2}-.0687203{col 37}{space 2} .0533815{col 48}{space 1}   -1.29{col 57}{space 3}0.199{col 65}{space 4}-.1737049{col 78}{space 3} .0362643
{txt}{space 20}Age {c |}{col 25}{res}{space 2}-.0024902{col 37}{space 2} .0024332{col 48}{space 1}   -1.02{col 57}{space 3}0.307{col 65}{space 4}-.0072697{col 78}{space 3} .0022893
{txt}{space 16}edu_age {c |}{col 25}{res}{space 2}-.0456014{col 37}{space 2} .0170501{col 48}{space 1}   -2.67{col 57}{space 3}0.008{col 65}{space 4}-.0791449{col 78}{space 3} -.012058
{txt}{space 23} {c |}
{space 12}SocialGrade {c |}
{space 20}C1  {c |}{col 25}{res}{space 2} -.035829{col 37}{space 2}  .061055{col 48}{space 1}   -0.59{col 57}{space 3}0.558{col 65}{space 4}-.1557936{col 78}{space 3} .0841357
{txt}{space 20}C2  {c |}{col 25}{res}{space 2}-.0572066{col 37}{space 2} .0854376{col 48}{space 1}   -0.67{col 57}{space 3}0.503{col 65}{space 4}-.2250276{col 78}{space 3} .1106143
{txt}{space 20}DE  {c |}{col 25}{res}{space 2}-.0235533{col 37}{space 2} .0827109{col 48}{space 1}   -0.28{col 57}{space 3}0.776{col 65}{space 4}-.1863116{col 78}{space 3} .1392049
{txt}{space 23} {c |}
{space 12}work_status {c |}
{space 5}working part time  {c |}{col 25}{res}{space 2}-.0377542{col 37}{space 2}  .077375{col 48}{space 1}   -0.49{col 57}{space 3}0.626{col 65}{space 4}-.1898264{col 78}{space 3}  .114318
{txt}{space 5}full time student  {c |}{col 25}{res}{space 2}-.1352111{col 37}{space 2} .1441623{col 48}{space 1}   -0.94{col 57}{space 3}0.349{col 65}{space 4}-.4187374{col 78}{space 3} .1483152
{txt}{space 15}retired  {c |}{col 25}{res}{space 2} .0974429{col 37}{space 2} .0821828{col 48}{space 1}    1.19{col 57}{space 3}0.236{col 65}{space 4}-.0639921{col 78}{space 3} .2588779
{txt}{space 12}unemployed  {c |}{col 25}{res}{space 2}-4.96e-06{col 37}{space 2} .1370426{col 48}{space 1}   -0.00{col 57}{space 3}1.000{col 65}{space 4}-.2693661{col 78}{space 3} .2693562
{txt}{space 11}not working  {c |}{col 25}{res}{space 2} .0473528{col 37}{space 2} .1031011{col 48}{space 1}    0.46{col 57}{space 3}0.646{col 65}{space 4}-.1554336{col 78}{space 3} .2501393
{txt}{space 23} {c |}
{space 17}UKborn {c |}{col 25}{res}{space 2} .2097358{col 37}{space 2} .3490169{col 48}{space 1}    0.60{col 57}{space 3}0.548{col 65}{space 4}-.4756573{col 78}{space 3} .8951289
{txt}{space 13}authvalues {c |}{col 25}{res}{space 2} .2326819{col 37}{space 2} .0461528{col 48}{space 1}    5.04{col 57}{space 3}0.000{col 65}{space 4} .1418538{col 78}{space 3} .3235101
{txt}{space 16}selfest {c |}{col 25}{res}{space 2} .3457289{col 37}{space 2} .1009437{col 48}{space 1}    3.42{col 57}{space 3}0.001{col 65}{space 4} .1463401{col 78}{space 3} .5451177
{txt}{space 18}_cons {c |}{col 25}{res}{space 2} 1.902988{col 37}{space 2} .5400321{col 48}{space 1}    3.52{col 57}{space 3}0.000{col 65}{space 4} .8418074{col 78}{space 3} 2.964169
{txt}{hline 24}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHMus c.threat4##treatment female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       646

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 647.524069
{txt}{col 1}Number of PSUs{col 19}= {res}      646
{txt}{col 49}Average RVI{col 67}= {res}    0.1119
{txt}{col 49}Largest FMI{col 67}= {res}    0.1832
{txt}{col 49}Complete DF{col 67}= {res}       645
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    186.22
{txt}{col 49}        avg{col 67}= {res}    387.98
{txt}{col 49}        max{col 67}= {res}    615.50
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  17{txt},{res}  615.2{txt}){col 67}= {res}     19.22
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}                  GHMus{col 25}{c |}      Coef.{col 37}   Std. Err.{col 49}      t{col 57}   P>|t|{col 65}     [95% Con{col 78}f. Interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 16}threat4 {c |}{col 25}{res}{space 2} .2951302{col 37}{space 2} .0373624{col 48}{space 1}    7.90{col 57}{space 3}0.000{col 65}{space 4} .2214221{col 78}{space 3} .3688382
{txt}{space 23} {c |}
{space 14}treatment {c |}
received coupled items  {c |}{col 25}{res}{space 2} .1507045{col 37}{space 2} .1637156{col 48}{space 1}    0.92{col 57}{space 3}0.358{col 65}{space 4}-.1717229{col 78}{space 3} .4731319
{txt}{space 23} {c |}
{space 4}treatment#c.threat4 {c |}
received coupled items  {c |}{col 25}{res}{space 2}-.0123539{col 37}{space 2} .0543496{col 48}{space 1}   -0.23{col 57}{space 3}0.820{col 65}{space 4}-.1194063{col 78}{space 3} .0946984
{txt}{space 23} {c |}
{space 17}female {c |}{col 25}{res}{space 2} -.057425{col 37}{space 2} .0514226{col 48}{space 1}   -1.12{col 57}{space 3}0.265{col 65}{space 4}-.1585552{col 78}{space 3} .0437052
{txt}{space 20}Age {c |}{col 25}{res}{space 2}-.0025566{col 37}{space 2}  .002463{col 48}{space 1}   -1.04{col 57}{space 3}0.300{col 65}{space 4}-.0073949{col 78}{space 3} .0022816
{txt}{space 16}edu_age {c |}{col 25}{res}{space 2}-.0339972{col 37}{space 2} .0161622{col 48}{space 1}   -2.10{col 57}{space 3}0.036{col 65}{space 4}-.0658008{col 78}{space 3}-.0021936
{txt}{space 23} {c |}
{space 12}SocialGrade {c |}
{space 20}C1  {c |}{col 25}{res}{space 2}-.0699401{col 37}{space 2} .0609091{col 48}{space 1}   -1.15{col 57}{space 3}0.251{col 65}{space 4}-.1896346{col 78}{space 3} .0497544
{txt}{space 20}C2  {c |}{col 25}{res}{space 2}-.0351042{col 37}{space 2}  .085552{col 48}{space 1}   -0.41{col 57}{space 3}0.682{col 65}{space 4}-.2031567{col 78}{space 3} .1329483
{txt}{space 20}DE  {c |}{col 25}{res}{space 2}-.0011011{col 37}{space 2} .0826947{col 48}{space 1}   -0.01{col 57}{space 3}0.989{col 65}{space 4}-.1638444{col 78}{space 3} .1616423
{txt}{space 23} {c |}
{space 12}work_status {c |}
{space 5}working part time  {c |}{col 25}{res}{space 2}-.0619545{col 37}{space 2} .0750393{col 48}{space 1}   -0.83{col 57}{space 3}0.409{col 65}{space 4}-.2094242{col 78}{space 3} .0855152
{txt}{space 5}full time student  {c |}{col 25}{res}{space 2}-.0005755{col 37}{space 2} .1652583{col 48}{space 1}   -0.00{col 57}{space 3}0.997{col 65}{space 4}-.3254193{col 78}{space 3} .3242683
{txt}{space 15}retired  {c |}{col 25}{res}{space 2} .0807731{col 37}{space 2} .0800597{col 48}{space 1}    1.01{col 57}{space 3}0.313{col 65}{space 4}-.0764926{col 78}{space 3} .2380387
{txt}{space 12}unemployed  {c |}{col 25}{res}{space 2} .0393584{col 37}{space 2} .1311802{col 48}{space 1}    0.30{col 57}{space 3}0.764{col 65}{space 4} -.218482{col 78}{space 3} .2971988
{txt}{space 11}not working  {c |}{col 25}{res}{space 2} .0370049{col 37}{space 2} .1065986{col 48}{space 1}    0.35{col 57}{space 3}0.729{col 65}{space 4}-.1726319{col 78}{space 3} .2466417
{txt}{space 23} {c |}
{space 17}UKborn {c |}{col 25}{res}{space 2}-.1067012{col 37}{space 2} .3317019{col 48}{space 1}   -0.32{col 57}{space 3}0.748{col 65}{space 4}-.7581059{col 78}{space 3} .5447035
{txt}{space 13}authvalues {c |}{col 25}{res}{space 2} .2138858{col 37}{space 2} .0464703{col 48}{space 1}    4.60{col 57}{space 3}0.000{col 65}{space 4} .1223966{col 78}{space 3}  .305375
{txt}{space 16}selfest {c |}{col 25}{res}{space 2}  .254379{col 37}{space 2} .0991251{col 48}{space 1}    2.57{col 57}{space 3}0.011{col 65}{space 4}  .058913{col 78}{space 3}  .449845
{txt}{space 18}_cons {c |}{col 25}{res}{space 2} 1.689041{col 37}{space 2} .5004241{col 48}{space 1}    3.38{col 57}{space 3}0.001{col 65}{space 4} .7059133{col 78}{space 3} 2.672168
{txt}{hline 24}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHMus c.threat5##treatment female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       647

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 648.731731
{txt}{col 1}Number of PSUs{col 19}= {res}      647
{txt}{col 49}Average RVI{col 67}= {res}    0.0965
{txt}{col 49}Largest FMI{col 67}= {res}    0.1883
{txt}{col 49}Complete DF{col 67}= {res}       646
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    179.44
{txt}{col 49}        avg{col 67}= {res}    457.05
{txt}{col 49}        max{col 67}= {res}    620.03
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  17{txt},{res}  622.2{txt}){col 67}= {res}     15.82
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}                  GHMus{col 25}{c |}      Coef.{col 37}   Std. Err.{col 49}      t{col 57}   P>|t|{col 65}     [95% Con{col 78}f. Interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 16}threat5 {c |}{col 25}{res}{space 2} .0205822{col 37}{space 2} .0562469{col 48}{space 1}    0.37{col 57}{space 3}0.715{col 65}{space 4}-.0898887{col 78}{space 3} .1310531
{txt}{space 23} {c |}
{space 14}treatment {c |}
received coupled items  {c |}{col 25}{res}{space 2}-.7377243{col 37}{space 2} .2105355{col 48}{space 1}   -3.50{col 57}{space 3}0.000{col 65}{space 4}-1.151289{col 78}{space 3}-.3241593
{txt}{space 23} {c |}
{space 4}treatment#c.threat5 {c |}
received coupled items  {c |}{col 25}{res}{space 2} .2984754{col 37}{space 2} .0678902{col 48}{space 1}    4.40{col 57}{space 3}0.000{col 65}{space 4} .1651214{col 78}{space 3} .4318293
{txt}{space 23} {c |}
{space 17}female {c |}{col 25}{res}{space 2}-.0665933{col 37}{space 2}  .053628{col 48}{space 1}   -1.24{col 57}{space 3}0.215{col 65}{space 4}-.1720507{col 78}{space 3}  .038864
{txt}{space 20}Age {c |}{col 25}{res}{space 2}-.0018266{col 37}{space 2} .0025466{col 48}{space 1}   -0.72{col 57}{space 3}0.474{col 65}{space 4}-.0068289{col 78}{space 3} .0031757
{txt}{space 16}edu_age {c |}{col 25}{res}{space 2}-.0591699{col 37}{space 2} .0171316{col 48}{space 1}   -3.45{col 57}{space 3}0.001{col 65}{space 4} -.092855{col 78}{space 3}-.0254847
{txt}{space 23} {c |}
{space 12}SocialGrade {c |}
{space 20}C1  {c |}{col 25}{res}{space 2}-.0436062{col 37}{space 2}  .062825{col 48}{space 1}   -0.69{col 57}{space 3}0.488{col 65}{space 4}-.1670347{col 78}{space 3} .0798224
{txt}{space 20}C2  {c |}{col 25}{res}{space 2}-.0624563{col 37}{space 2} .0911174{col 48}{space 1}   -0.69{col 57}{space 3}0.493{col 65}{space 4}-.2414319{col 78}{space 3} .1165193
{txt}{space 20}DE  {c |}{col 25}{res}{space 2} .0156286{col 37}{space 2}  .082716{col 48}{space 1}    0.19{col 57}{space 3}0.850{col 65}{space 4}-.1471547{col 78}{space 3} .1784119
{txt}{space 23} {c |}
{space 12}work_status {c |}
{space 5}working part time  {c |}{col 25}{res}{space 2}-.0741793{col 37}{space 2} .0788474{col 48}{space 1}   -0.94{col 57}{space 3}0.347{col 65}{space 4}-.2291156{col 78}{space 3} .0807571
{txt}{space 5}full time student  {c |}{col 25}{res}{space 2}-.1150015{col 37}{space 2} .1627939{col 48}{space 1}   -0.71{col 57}{space 3}0.480{col 65}{space 4}-.4350033{col 78}{space 3} .2050004
{txt}{space 15}retired  {c |}{col 25}{res}{space 2}  .077704{col 37}{space 2} .0817746{col 48}{space 1}    0.95{col 57}{space 3}0.342{col 65}{space 4}-.0829334{col 78}{space 3} .2383415
{txt}{space 12}unemployed  {c |}{col 25}{res}{space 2}-.0222067{col 37}{space 2} .1418921{col 48}{space 1}   -0.16{col 57}{space 3}0.876{col 65}{space 4}-.3010556{col 78}{space 3} .2566423
{txt}{space 11}not working  {c |}{col 25}{res}{space 2} .0197084{col 37}{space 2} .1055052{col 48}{space 1}    0.19{col 57}{space 3}0.852{col 65}{space 4}-.1878089{col 78}{space 3} .2272256
{txt}{space 23} {c |}
{space 17}UKborn {c |}{col 25}{res}{space 2} .2147397{col 37}{space 2} .3358942{col 48}{space 1}    0.64{col 57}{space 3}0.523{col 65}{space 4}-.4448884{col 78}{space 3} .8743677
{txt}{space 13}authvalues {c |}{col 25}{res}{space 2}  .239135{col 37}{space 2} .0477502{col 48}{space 1}    5.01{col 57}{space 3}0.000{col 65}{space 4} .1451534{col 78}{space 3} .3331166
{txt}{space 16}selfest {c |}{col 25}{res}{space 2} .3403173{col 37}{space 2} .1032758{col 48}{space 1}    3.30{col 57}{space 3}0.001{col 65}{space 4}  .136526{col 78}{space 3} .5441087
{txt}{space 18}_cons {c |}{col 25}{res}{space 2} 2.550734{col 37}{space 2} .5558779{col 48}{space 1}    4.59{col 57}{space 3}0.000{col 65}{space 4} 1.458958{col 78}{space 3} 3.642509
{txt}{hline 24}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. mi estimate: svy: reg GHEEur c.threat1##treatment female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       634

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 636.222547
{txt}{col 1}Number of PSUs{col 19}= {res}      634
{txt}{col 49}Average RVI{col 67}= {res}    0.1407
{txt}{col 49}Largest FMI{col 67}= {res}    0.2242
{txt}{col 49}Complete DF{col 67}= {res}       633
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    139.19
{txt}{col 49}        avg{col 67}= {res}    348.54
{txt}{col 49}        max{col 67}= {res}    611.20
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  17{txt},{res}  590.3{txt}){col 67}= {res}     11.20
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}                 GHEEur{col 25}{c |}      Coef.{col 37}   Std. Err.{col 49}      t{col 57}   P>|t|{col 65}     [95% Con{col 78}f. Interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 16}threat1 {c |}{col 25}{res}{space 2} .0948408{col 37}{space 2} .0390423{col 48}{space 1}    2.43{col 57}{space 3}0.016{col 65}{space 4} .0178397{col 78}{space 3}  .171842
{txt}{space 23} {c |}
{space 14}treatment {c |}
received coupled items  {c |}{col 25}{res}{space 2}-.3892019{col 37}{space 2} .1349971{col 48}{space 1}   -2.88{col 57}{space 3}0.004{col 65}{space 4}-.6550336{col 78}{space 3}-.1233703
{txt}{space 23} {c |}
{space 4}treatment#c.threat1 {c |}
received coupled items  {c |}{col 25}{res}{space 2} .2121087{col 37}{space 2} .0569081{col 48}{space 1}    3.73{col 57}{space 3}0.000{col 65}{space 4}  .100256{col 78}{space 3} .3239613
{txt}{space 23} {c |}
{space 17}female {c |}{col 25}{res}{space 2}-.0017415{col 37}{space 2} .0493197{col 48}{space 1}   -0.04{col 57}{space 3}0.972{col 65}{space 4}-.0986874{col 78}{space 3} .0952044
{txt}{space 20}Age {c |}{col 25}{res}{space 2}-.0028065{col 37}{space 2} .0024246{col 48}{space 1}   -1.16{col 57}{space 3}0.248{col 65}{space 4}-.0075708{col 78}{space 3} .0019577
{txt}{space 16}edu_age {c |}{col 25}{res}{space 2}-.0670657{col 37}{space 2} .0143842{col 48}{space 1}   -4.66{col 57}{space 3}0.000{col 65}{space 4}-.0953572{col 78}{space 3}-.0387741
{txt}{space 23} {c |}
{space 12}SocialGrade {c |}
{space 20}C1  {c |}{col 25}{res}{space 2}-.0247525{col 37}{space 2} .0580873{col 48}{space 1}   -0.43{col 57}{space 3}0.670{col 65}{space 4}-.1391437{col 78}{space 3} .0896387
{txt}{space 20}C2  {c |}{col 25}{res}{space 2} -.050607{col 37}{space 2} .0939245{col 48}{space 1}   -0.54{col 57}{space 3}0.590{col 65}{space 4}-.2351164{col 78}{space 3} .1339025
{txt}{space 20}DE  {c |}{col 25}{res}{space 2}-.0042362{col 37}{space 2} .0714639{col 48}{space 1}   -0.06{col 57}{space 3}0.953{col 65}{space 4}-.1446127{col 78}{space 3} .1361404
{txt}{space 23} {c |}
{space 12}work_status {c |}
{space 5}working part time  {c |}{col 25}{res}{space 2}-.0753853{col 37}{space 2} .0778213{col 48}{space 1}   -0.97{col 57}{space 3}0.334{col 65}{space 4}-.2292501{col 78}{space 3} .0784795
{txt}{space 5}full time student  {c |}{col 25}{res}{space 2}-.2299939{col 37}{space 2} .1914564{col 48}{space 1}   -1.20{col 57}{space 3}0.231{col 65}{space 4}-.6078318{col 78}{space 3}  .147844
{txt}{space 15}retired  {c |}{col 25}{res}{space 2} .0855334{col 37}{space 2} .0777713{col 48}{space 1}    1.10{col 57}{space 3}0.272{col 65}{space 4}-.0672884{col 78}{space 3} .2383551
{txt}{space 12}unemployed  {c |}{col 25}{res}{space 2}-.1074485{col 37}{space 2} .1414293{col 48}{space 1}   -0.76{col 57}{space 3}0.448{col 65}{space 4}-.3853518{col 78}{space 3} .1704548
{txt}{space 11}not working  {c |}{col 25}{res}{space 2} .1277036{col 37}{space 2} .1162594{col 48}{space 1}    1.10{col 57}{space 3}0.273{col 65}{space 4}-.1014808{col 78}{space 3}  .356888
{txt}{space 23} {c |}
{space 17}UKborn {c |}{col 25}{res}{space 2} .0247843{col 37}{space 2} .1657349{col 48}{space 1}    0.15{col 57}{space 3}0.881{col 65}{space 4}-.3006947{col 78}{space 3} .3502634
{txt}{space 13}authvalues {c |}{col 25}{res}{space 2} .1704723{col 37}{space 2} .0444315{col 48}{space 1}    3.84{col 57}{space 3}0.000{col 65}{space 4} .0826401{col 78}{space 3} .2583046
{txt}{space 16}selfest {c |}{col 25}{res}{space 2} .2232269{col 37}{space 2}  .099782{col 48}{space 1}    2.24{col 57}{space 3}0.026{col 65}{space 4} .0263781{col 78}{space 3} .4200756
{txt}{space 18}_cons {c |}{col 25}{res}{space 2} 2.781692{col 37}{space 2} .4068431{col 48}{space 1}    6.84{col 57}{space 3}0.000{col 65}{space 4}  1.98193{col 78}{space 3} 3.581455
{txt}{hline 24}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHEEur c.threat2##treatment female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       637

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 641.353009
{txt}{col 1}Number of PSUs{col 19}= {res}      637
{txt}{col 49}Average RVI{col 67}= {res}    0.1314
{txt}{col 49}Largest FMI{col 67}= {res}    0.2793
{txt}{col 49}Complete DF{col 67}= {res}       636
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}     99.13
{txt}{col 49}        avg{col 67}= {res}    371.23
{txt}{col 49}        max{col 67}= {res}    624.88
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  17{txt},{res}  597.0{txt}){col 67}= {res}      9.93
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}                 GHEEur{col 25}{c |}      Coef.{col 37}   Std. Err.{col 49}      t{col 57}   P>|t|{col 65}     [95% Con{col 78}f. Interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 16}threat2 {c |}{col 25}{res}{space 2} .0675038{col 37}{space 2} .0422934{col 48}{space 1}    1.60{col 57}{space 3}0.111{col 65}{space 4}-.0157091{col 78}{space 3} .1507166
{txt}{space 23} {c |}
{space 14}treatment {c |}
received coupled items  {c |}{col 25}{res}{space 2}-.3985367{col 37}{space 2} .1630015{col 48}{space 1}   -2.44{col 57}{space 3}0.015{col 65}{space 4} -.718927{col 78}{space 3}-.0781464
{txt}{space 23} {c |}
{space 4}treatment#c.threat2 {c |}
received coupled items  {c |}{col 25}{res}{space 2} .2087595{col 37}{space 2} .0586555{col 48}{space 1}    3.56{col 57}{space 3}0.000{col 65}{space 4} .0935358{col 78}{space 3} .3239832
{txt}{space 23} {c |}
{space 17}female {c |}{col 25}{res}{space 2}-.0179343{col 37}{space 2} .0477203{col 48}{space 1}   -0.38{col 57}{space 3}0.707{col 65}{space 4}-.1117253{col 78}{space 3} .0758567
{txt}{space 20}Age {c |}{col 25}{res}{space 2}-.0028819{col 37}{space 2} .0024986{col 48}{space 1}   -1.15{col 57}{space 3}0.249{col 65}{space 4}-.0077916{col 78}{space 3} .0020277
{txt}{space 16}edu_age {c |}{col 25}{res}{space 2}-.0690981{col 37}{space 2} .0147849{col 48}{space 1}   -4.67{col 57}{space 3}0.000{col 65}{space 4}-.0981715{col 78}{space 3}-.0400247
{txt}{space 23} {c |}
{space 12}SocialGrade {c |}
{space 20}C1  {c |}{col 25}{res}{space 2}-.0260368{col 37}{space 2} .0586309{col 48}{space 1}   -0.44{col 57}{space 3}0.657{col 65}{space 4}-.1414792{col 78}{space 3} .0894056
{txt}{space 20}C2  {c |}{col 25}{res}{space 2}-.0546819{col 37}{space 2} .0858967{col 48}{space 1}   -0.64{col 57}{space 3}0.525{col 65}{space 4}-.2234385{col 78}{space 3} .1140746
{txt}{space 20}DE  {c |}{col 25}{res}{space 2}  .001885{col 37}{space 2} .0735279{col 48}{space 1}    0.03{col 57}{space 3}0.980{col 65}{space 4}-.1425448{col 78}{space 3} .1463148
{txt}{space 23} {c |}
{space 12}work_status {c |}
{space 5}working part time  {c |}{col 25}{res}{space 2}-.1041616{col 37}{space 2}  .077403{col 48}{space 1}   -1.35{col 57}{space 3}0.180{col 65}{space 4}-.2570557{col 78}{space 3} .0487325
{txt}{space 5}full time student  {c |}{col 25}{res}{space 2}-.2206267{col 37}{space 2} .1584023{col 48}{space 1}   -1.39{col 57}{space 3}0.167{col 65}{space 4}-.5349261{col 78}{space 3} .0936727
{txt}{space 15}retired  {c |}{col 25}{res}{space 2} .1014359{col 37}{space 2} .0807457{col 48}{space 1}    1.26{col 57}{space 3}0.210{col 65}{space 4}-.0572326{col 78}{space 3} .2601045
{txt}{space 12}unemployed  {c |}{col 25}{res}{space 2}-.1412439{col 37}{space 2} .1560883{col 48}{space 1}   -0.90{col 57}{space 3}0.366{col 65}{space 4}-.4479279{col 78}{space 3} .1654402
{txt}{space 11}not working  {c |}{col 25}{res}{space 2} .1368108{col 37}{space 2} .1195912{col 48}{space 1}    1.14{col 57}{space 3}0.254{col 65}{space 4}-.0988348{col 78}{space 3} .3724563
{txt}{space 23} {c |}
{space 17}UKborn {c |}{col 25}{res}{space 2} .1028031{col 37}{space 2}  .219684{col 48}{space 1}    0.47{col 57}{space 3}0.640{col 65}{space 4}-.3286052{col 78}{space 3} .5342113
{txt}{space 13}authvalues {c |}{col 25}{res}{space 2} .1864718{col 37}{space 2} .0445448{col 48}{space 1}    4.19{col 57}{space 3}0.000{col 65}{space 4} .0985051{col 78}{space 3} .2744386
{txt}{space 16}selfest {c |}{col 25}{res}{space 2} .2193642{col 37}{space 2} .1012102{col 48}{space 1}    2.17{col 57}{space 3}0.032{col 65}{space 4} .0196467{col 78}{space 3} .4190817
{txt}{space 18}_cons {c |}{col 25}{res}{space 2} 2.751657{col 37}{space 2} .4616509{col 48}{space 1}    5.96{col 57}{space 3}0.000{col 65}{space 4} 1.844076{col 78}{space 3} 3.659238
{txt}{hline 24}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHEEur c.threat3##treatment female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       638

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 642.353009
{txt}{col 1}Number of PSUs{col 19}= {res}      638
{txt}{col 49}Average RVI{col 67}= {res}    0.1319
{txt}{col 49}Largest FMI{col 67}= {res}    0.2475
{txt}{col 49}Complete DF{col 67}= {res}       637
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    120.01
{txt}{col 49}        avg{col 67}= {res}    368.22
{txt}{col 49}        max{col 67}= {res}    613.64
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  17{txt},{res}  598.1{txt}){col 67}= {res}     11.94
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}                 GHEEur{col 25}{c |}      Coef.{col 37}   Std. Err.{col 49}      t{col 57}   P>|t|{col 65}     [95% Con{col 78}f. Interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 16}threat3 {c |}{col 25}{res}{space 2}  .140346{col 37}{space 2} .0365642{col 48}{space 1}    3.84{col 57}{space 3}0.000{col 65}{space 4} .0683618{col 78}{space 3} .2123301
{txt}{space 23} {c |}
{space 14}treatment {c |}
received coupled items  {c |}{col 25}{res}{space 2}-.2495318{col 37}{space 2} .1557059{col 48}{space 1}   -1.60{col 57}{space 3}0.110{col 65}{space 4}-.5556625{col 78}{space 3} .0565989
{txt}{space 23} {c |}
{space 4}treatment#c.threat3 {c |}
received coupled items  {c |}{col 25}{res}{space 2} .1436784{col 37}{space 2} .0556049{col 48}{space 1}    2.58{col 57}{space 3}0.010{col 65}{space 4} .0344152{col 78}{space 3} .2529416
{txt}{space 23} {c |}
{space 17}female {c |}{col 25}{res}{space 2}-.0287332{col 37}{space 2} .0489605{col 48}{space 1}   -0.59{col 57}{space 3}0.558{col 65}{space 4}-.1249843{col 78}{space 3}  .067518
{txt}{space 20}Age {c |}{col 25}{res}{space 2}-.0028871{col 37}{space 2} .0024528{col 48}{space 1}   -1.18{col 57}{space 3}0.240{col 65}{space 4}-.0077066{col 78}{space 3} .0019323
{txt}{space 16}edu_age {c |}{col 25}{res}{space 2}-.0561831{col 37}{space 2} .0146419{col 48}{space 1}   -3.84{col 57}{space 3}0.000{col 65}{space 4}-.0849755{col 78}{space 3}-.0273907
{txt}{space 23} {c |}
{space 12}SocialGrade {c |}
{space 20}C1  {c |}{col 25}{res}{space 2}-.0071129{col 37}{space 2} .0575929{col 48}{space 1}   -0.12{col 57}{space 3}0.902{col 65}{space 4} -.120513{col 78}{space 3} .1062871
{txt}{space 20}C2  {c |}{col 25}{res}{space 2}-.0343495{col 37}{space 2} .0876858{col 48}{space 1}   -0.39{col 57}{space 3}0.695{col 65}{space 4}-.2066103{col 78}{space 3} .1379114
{txt}{space 20}DE  {c |}{col 25}{res}{space 2}  .005122{col 37}{space 2} .0742653{col 48}{space 1}    0.07{col 57}{space 3}0.945{col 65}{space 4}-.1407606{col 78}{space 3} .1510046
{txt}{space 23} {c |}
{space 12}work_status {c |}
{space 5}working part time  {c |}{col 25}{res}{space 2}-.0802775{col 37}{space 2} .0787824{col 48}{space 1}   -1.02{col 57}{space 3}0.310{col 65}{space 4}-.2359985{col 78}{space 3} .0754434
{txt}{space 5}full time student  {c |}{col 25}{res}{space 2}-.2517569{col 37}{space 2} .1673004{col 48}{space 1}   -1.50{col 57}{space 3}0.135{col 65}{space 4}-.5829998{col 78}{space 3} .0794859
{txt}{space 15}retired  {c |}{col 25}{res}{space 2} .0697598{col 37}{space 2} .0784936{col 48}{space 1}    0.89{col 57}{space 3}0.375{col 65}{space 4}-.0844693{col 78}{space 3} .2239889
{txt}{space 12}unemployed  {c |}{col 25}{res}{space 2}  -.11044{col 37}{space 2} .1545209{col 48}{space 1}   -0.71{col 57}{space 3}0.475{col 65}{space 4}-.4140179{col 78}{space 3}  .193138
{txt}{space 11}not working  {c |}{col 25}{res}{space 2} .1489314{col 37}{space 2} .1169623{col 48}{space 1}    1.27{col 57}{space 3}0.204{col 65}{space 4}-.0815557{col 78}{space 3} .3794185
{txt}{space 23} {c |}
{space 17}UKborn {c |}{col 25}{res}{space 2} .0899479{col 37}{space 2} .1637624{col 48}{space 1}    0.55{col 57}{space 3}0.583{col 65}{space 4}-.2316548{col 78}{space 3} .4115507
{txt}{space 13}authvalues {c |}{col 25}{res}{space 2} .1714313{col 37}{space 2} .0445658{col 48}{space 1}    3.85{col 57}{space 3}0.000{col 65}{space 4} .0833922{col 78}{space 3} .2594703
{txt}{space 16}selfest {c |}{col 25}{res}{space 2} .2784281{col 37}{space 2} .0975138{col 48}{space 1}    2.86{col 57}{space 3}0.005{col 65}{space 4} .0862247{col 78}{space 3} .4706315
{txt}{space 18}_cons {c |}{col 25}{res}{space 2} 2.348215{col 37}{space 2} .4141922{col 48}{space 1}    5.67{col 57}{space 3}0.000{col 65}{space 4} 1.534226{col 78}{space 3} 3.162204
{txt}{hline 24}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHEEur c.threat4##treatment female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest  
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       639

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 643.145346
{txt}{col 1}Number of PSUs{col 19}= {res}      639
{txt}{col 49}Average RVI{col 67}= {res}    0.1286
{txt}{col 49}Largest FMI{col 67}= {res}    0.2222
{txt}{col 49}Complete DF{col 67}= {res}       638
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    141.34
{txt}{col 49}        avg{col 67}= {res}    353.29
{txt}{col 49}        max{col 67}= {res}    622.83
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  17{txt},{res}  601.1{txt}){col 67}= {res}     12.21
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}                 GHEEur{col 25}{c |}      Coef.{col 37}   Std. Err.{col 49}      t{col 57}   P>|t|{col 65}     [95% Con{col 78}f. Interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 16}threat4 {c |}{col 25}{res}{space 2} .1859978{col 37}{space 2} .0335022{col 48}{space 1}    5.55{col 57}{space 3}0.000{col 65}{space 4} .1199571{col 78}{space 3} .2520386
{txt}{space 23} {c |}
{space 14}treatment {c |}
received coupled items  {c |}{col 25}{res}{space 2}-.0246504{col 37}{space 2} .1471777{col 48}{space 1}   -0.17{col 57}{space 3}0.867{col 65}{space 4} -.314189{col 78}{space 3} .2648881
{txt}{space 23} {c |}
{space 4}treatment#c.threat4 {c |}
received coupled items  {c |}{col 25}{res}{space 2} .0444713{col 37}{space 2} .0482937{col 48}{space 1}    0.92{col 57}{space 3}0.358{col 65}{space 4}-.0504575{col 78}{space 3} .1394001
{txt}{space 23} {c |}
{space 17}female {c |}{col 25}{res}{space 2}-.0109525{col 37}{space 2} .0488196{col 48}{space 1}   -0.22{col 57}{space 3}0.823{col 65}{space 4}-.1069036{col 78}{space 3} .0849986
{txt}{space 20}Age {c |}{col 25}{res}{space 2}-.0024726{col 37}{space 2} .0024166{col 48}{space 1}   -1.02{col 57}{space 3}0.307{col 65}{space 4}-.0072213{col 78}{space 3}  .002276
{txt}{space 16}edu_age {c |}{col 25}{res}{space 2}-.0522543{col 37}{space 2} .0147573{col 48}{space 1}   -3.54{col 57}{space 3}0.000{col 65}{space 4}-.0812957{col 78}{space 3}-.0232129
{txt}{space 23} {c |}
{space 12}SocialGrade {c |}
{space 20}C1  {c |}{col 25}{res}{space 2}-.0359147{col 37}{space 2}  .057103{col 48}{space 1}   -0.63{col 57}{space 3}0.530{col 65}{space 4}-.1484272{col 78}{space 3} .0765979
{txt}{space 20}C2  {c |}{col 25}{res}{space 2}-.0247892{col 37}{space 2} .0895243{col 48}{space 1}   -0.28{col 57}{space 3}0.782{col 65}{space 4}-.2006553{col 78}{space 3}  .151077
{txt}{space 20}DE  {c |}{col 25}{res}{space 2}-.0032022{col 37}{space 2} .0751556{col 48}{space 1}   -0.04{col 57}{space 3}0.966{col 65}{space 4}-.1508226{col 78}{space 3} .1444183
{txt}{space 23} {c |}
{space 12}work_status {c |}
{space 5}working part time  {c |}{col 25}{res}{space 2}-.1135034{col 37}{space 2} .0757997{col 48}{space 1}   -1.50{col 57}{space 3}0.136{col 65}{space 4}-.2633313{col 78}{space 3} .0363245
{txt}{space 5}full time student  {c |}{col 25}{res}{space 2}-.2011067{col 37}{space 2} .1935049{col 48}{space 1}   -1.04{col 57}{space 3}0.300{col 65}{space 4}-.5831367{col 78}{space 3} .1809233
{txt}{space 15}retired  {c |}{col 25}{res}{space 2} .0461712{col 37}{space 2} .0766631{col 48}{space 1}    0.60{col 57}{space 3}0.547{col 65}{space 4}-.1044735{col 78}{space 3} .1968159
{txt}{space 12}unemployed  {c |}{col 25}{res}{space 2}-.0720534{col 37}{space 2} .1492831{col 48}{space 1}   -0.48{col 57}{space 3}0.630{col 65}{space 4}-.3653854{col 78}{space 3} .2212786
{txt}{space 11}not working  {c |}{col 25}{res}{space 2} .1500451{col 37}{space 2} .1204646{col 48}{space 1}    1.25{col 57}{space 3}0.214{col 65}{space 4}-.0872673{col 78}{space 3} .3873574
{txt}{space 23} {c |}
{space 17}UKborn {c |}{col 25}{res}{space 2}-.0498738{col 37}{space 2} .2162885{col 48}{space 1}   -0.23{col 57}{space 3}0.818{col 65}{space 4}-.4746169{col 78}{space 3} .3748693
{txt}{space 13}authvalues {c |}{col 25}{res}{space 2} .1684867{col 37}{space 2} .0434285{col 48}{space 1}    3.88{col 57}{space 3}0.000{col 65}{space 4} .0826334{col 78}{space 3} .2543399
{txt}{space 16}selfest {c |}{col 25}{res}{space 2} .2117599{col 37}{space 2} .0975723{col 48}{space 1}    2.17{col 57}{space 3}0.031{col 65}{space 4} .0194644{col 78}{space 3} .4040554
{txt}{space 18}_cons {c |}{col 25}{res}{space 2} 2.264152{col 37}{space 2} .4323739{col 48}{space 1}    5.24{col 57}{space 3}0.000{col 65}{space 4} 1.414106{col 78}{space 3} 3.114197
{txt}{hline 24}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHEEur c.threat5##treatment female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest  
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       639

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 643.353009
{txt}{col 1}Number of PSUs{col 19}= {res}      639
{txt}{col 49}Average RVI{col 67}= {res}    0.1250
{txt}{col 49}Largest FMI{col 67}= {res}    0.2239
{txt}{col 49}Complete DF{col 67}= {res}       638
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    139.73
{txt}{col 49}        avg{col 67}= {res}    400.30
{txt}{col 49}        max{col 67}= {res}    623.85
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  17{txt},{res}  602.5{txt}){col 67}= {res}     11.40
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}                 GHEEur{col 25}{c |}      Coef.{col 37}   Std. Err.{col 49}      t{col 57}   P>|t|{col 65}     [95% Con{col 78}f. Interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 16}threat5 {c |}{col 25}{res}{space 2} .0537794{col 37}{space 2}  .041761{col 48}{space 1}    1.29{col 57}{space 3}0.198{col 65}{space 4}-.0282636{col 78}{space 3} .1358225
{txt}{space 23} {c |}
{space 14}treatment {c |}
received coupled items  {c |}{col 25}{res}{space 2}-.5491674{col 37}{space 2} .1584824{col 48}{space 1}   -3.47{col 57}{space 3}0.001{col 65}{space 4}  -.86052{col 78}{space 3}-.2378147
{txt}{space 23} {c |}
{space 4}treatment#c.threat5 {c |}
received coupled items  {c |}{col 25}{res}{space 2} .2369348{col 37}{space 2} .0545413{col 48}{space 1}    4.34{col 57}{space 3}0.000{col 65}{space 4} .1298143{col 78}{space 3} .3440552
{txt}{space 23} {c |}
{space 17}female {c |}{col 25}{res}{space 2}-.0290263{col 37}{space 2} .0487046{col 48}{space 1}   -0.60{col 57}{space 3}0.552{col 65}{space 4}-.1247764{col 78}{space 3} .0667239
{txt}{space 20}Age {c |}{col 25}{res}{space 2}-.0021311{col 37}{space 2} .0024056{col 48}{space 1}   -0.89{col 57}{space 3}0.376{col 65}{space 4}-.0068587{col 78}{space 3} .0025964
{txt}{space 16}edu_age {c |}{col 25}{res}{space 2}  -.06521{col 37}{space 2} .0140702{col 48}{space 1}   -4.63{col 57}{space 3}0.000{col 65}{space 4}-.0928691{col 78}{space 3} -.037551
{txt}{space 23} {c |}
{space 12}SocialGrade {c |}
{space 20}C1  {c |}{col 25}{res}{space 2}-.0136131{col 37}{space 2} .0575128{col 48}{space 1}   -0.24{col 57}{space 3}0.813{col 65}{space 4}-.1268703{col 78}{space 3} .0996442
{txt}{space 20}C2  {c |}{col 25}{res}{space 2}-.0460898{col 37}{space 2} .0921828{col 48}{space 1}   -0.50{col 57}{space 3}0.617{col 65}{space 4}-.2271719{col 78}{space 3} .1349924
{txt}{space 20}DE  {c |}{col 25}{res}{space 2}  .013461{col 37}{space 2}  .072254{col 48}{space 1}    0.19{col 57}{space 3}0.852{col 65}{space 4}-.1284753{col 78}{space 3} .1553973
{txt}{space 23} {c |}
{space 12}work_status {c |}
{space 5}working part time  {c |}{col 25}{res}{space 2}-.1023507{col 37}{space 2} .0756131{col 48}{space 1}   -1.35{col 57}{space 3}0.178{col 65}{space 4}-.2518445{col 78}{space 3} .0471431
{txt}{space 5}full time student  {c |}{col 25}{res}{space 2}  -.21999{col 37}{space 2} .1884862{col 48}{space 1}   -1.17{col 57}{space 3}0.245{col 65}{space 4}-.5921263{col 78}{space 3} .1521463
{txt}{space 15}retired  {c |}{col 25}{res}{space 2} .0626542{col 37}{space 2} .0756644{col 48}{space 1}    0.83{col 57}{space 3}0.408{col 65}{space 4}-.0860423{col 78}{space 3} .2113507
{txt}{space 12}unemployed  {c |}{col 25}{res}{space 2}-.1067862{col 37}{space 2} .1563911{col 48}{space 1}   -0.68{col 57}{space 3}0.495{col 65}{space 4}-.4140514{col 78}{space 3}  .200479
{txt}{space 11}not working  {c |}{col 25}{res}{space 2} .1414666{col 37}{space 2} .1182614{col 48}{space 1}    1.20{col 57}{space 3}0.233{col 65}{space 4}-.0916215{col 78}{space 3} .3745547
{txt}{space 23} {c |}
{space 17}UKborn {c |}{col 25}{res}{space 2} .0907452{col 37}{space 2} .2020973{col 48}{space 1}    0.45{col 57}{space 3}0.654{col 65}{space 4}-.3061282{col 78}{space 3} .4876185
{txt}{space 13}authvalues {c |}{col 25}{res}{space 2} .1698417{col 37}{space 2} .0445639{col 48}{space 1}    3.81{col 57}{space 3}0.000{col 65}{space 4} .0817356{col 78}{space 3} .2579479
{txt}{space 16}selfest {c |}{col 25}{res}{space 2} .2591027{col 37}{space 2} .0974814{col 48}{space 1}    2.66{col 57}{space 3}0.008{col 65}{space 4} .0669944{col 78}{space 3} .4512111
{txt}{space 18}_cons {c |}{col 25}{res}{space 2} 2.724206{col 37}{space 2} .4177289{col 48}{space 1}    6.52{col 57}{space 3}0.000{col 65}{space 4} 1.903625{col 78}{space 3} 3.544787
{txt}{hline 24}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. mi estimate: svy: reg GHwhite c.threat1##treatment female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       630

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 631.429543
{txt}{col 1}Number of PSUs{col 19}= {res}      630
{txt}{col 49}Average RVI{col 67}= {res}    0.1303
{txt}{col 49}Largest FMI{col 67}= {res}    0.2896
{txt}{col 49}Complete DF{col 67}= {res}       629
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}     93.30
{txt}{col 49}        avg{col 67}= {res}    401.99
{txt}{col 49}        max{col 67}= {res}    607.41
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  17{txt},{res}  593.7{txt}){col 67}= {res}      1.68
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0423

{txt}{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}                GHwhite{col 25}{c |}      Coef.{col 37}   Std. Err.{col 49}      t{col 57}   P>|t|{col 65}     [95% Con{col 78}f. Interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 16}threat1 {c |}{col 25}{res}{space 2}  .171251{col 37}{space 2} .0931831{col 48}{space 1}    1.84{col 57}{space 3}0.067{col 65}{space 4}-.0117881{col 78}{space 3}   .35429
{txt}{space 23} {c |}
{space 14}treatment {c |}
received coupled items  {c |}{col 25}{res}{space 2} .5266224{col 37}{space 2} .3232725{col 48}{space 1}    1.63{col 57}{space 3}0.104{col 65}{space 4}-.1086625{col 78}{space 3} 1.161907
{txt}{space 23} {c |}
{space 4}treatment#c.threat1 {c |}
received coupled items  {c |}{col 25}{res}{space 2}-.2423616{col 37}{space 2} .1259891{col 48}{space 1}   -1.92{col 57}{space 3}0.055{col 65}{space 4}-.4900439{col 78}{space 3} .0053208
{txt}{space 23} {c |}
{space 17}female {c |}{col 25}{res}{space 2} .2052526{col 37}{space 2} .1064242{col 48}{space 1}    1.93{col 57}{space 3}0.054{col 65}{space 4}-.0037514{col 78}{space 3} .4142566
{txt}{space 20}Age {c |}{col 25}{res}{space 2}-.0190523{col 37}{space 2} .0062521{col 48}{space 1}   -3.05{col 57}{space 3}0.002{col 65}{space 4}-.0313389{col 78}{space 3}-.0067657
{txt}{space 16}edu_age {c |}{col 25}{res}{space 2}-.0189329{col 37}{space 2} .0370235{col 48}{space 1}   -0.51{col 57}{space 3}0.609{col 65}{space 4}-.0916976{col 78}{space 3} .0538318
{txt}{space 23} {c |}
{space 12}SocialGrade {c |}
{space 20}C1  {c |}{col 25}{res}{space 2} .0144728{col 37}{space 2} .1333637{col 48}{space 1}    0.11{col 57}{space 3}0.914{col 65}{space 4}-.2477357{col 78}{space 3} .2766813
{txt}{space 20}C2  {c |}{col 25}{res}{space 2} .0466483{col 37}{space 2} .2025677{col 48}{space 1}    0.23{col 57}{space 3}0.818{col 65}{space 4}-.3512902{col 78}{space 3} .4445868
{txt}{space 20}DE  {c |}{col 25}{res}{space 2}-.0182661{col 37}{space 2} .1741068{col 48}{space 1}   -0.10{col 57}{space 3}0.916{col 65}{space 4}-.3603615{col 78}{space 3} .3238293
{txt}{space 23} {c |}
{space 12}work_status {c |}
{space 5}working part time  {c |}{col 25}{res}{space 2} .1136342{col 37}{space 2} .1761132{col 48}{space 1}    0.65{col 57}{space 3}0.519{col 65}{space 4}-.2322818{col 78}{space 3} .4595503
{txt}{space 5}full time student  {c |}{col 25}{res}{space 2}-.0681859{col 37}{space 2} .3080415{col 48}{space 1}   -0.22{col 57}{space 3}0.825{col 65}{space 4}-.6742981{col 78}{space 3} .5379264
{txt}{space 15}retired  {c |}{col 25}{res}{space 2} .3180363{col 37}{space 2} .1790542{col 48}{space 1}    1.78{col 57}{space 3}0.077{col 65}{space 4}-.0343323{col 78}{space 3} .6704048
{txt}{space 12}unemployed  {c |}{col 25}{res}{space 2} .1464143{col 37}{space 2} .2882406{col 48}{space 1}    0.51{col 57}{space 3}0.612{col 65}{space 4}-.4206629{col 78}{space 3} .7134915
{txt}{space 11}not working  {c |}{col 25}{res}{space 2} .3194407{col 37}{space 2} .2639971{col 48}{space 1}    1.21{col 57}{space 3}0.227{col 65}{space 4} -.199154{col 78}{space 3} .8380353
{txt}{space 23} {c |}
{space 17}UKborn {c |}{col 25}{res}{space 2} .1020973{col 37}{space 2} .2222031{col 48}{space 1}    0.46{col 57}{space 3}0.647{col 65}{space 4}-.3391352{col 78}{space 3} .5433299
{txt}{space 13}authvalues {c |}{col 25}{res}{space 2} .1784883{col 37}{space 2} .1080535{col 48}{space 1}    1.65{col 57}{space 3}0.101{col 65}{space 4}-.0349842{col 78}{space 3} .3919608
{txt}{space 16}selfest {c |}{col 25}{res}{space 2} .0597403{col 37}{space 2} .2481862{col 48}{space 1}    0.24{col 57}{space 3}0.810{col 65}{space 4}-.4290658{col 78}{space 3} .5485465
{txt}{space 18}_cons {c |}{col 25}{res}{space 2} 2.415205{col 37}{space 2} 1.018393{col 48}{space 1}    2.37{col 57}{space 3}0.018{col 65}{space 4} .4131058{col 78}{space 3} 4.417304
{txt}{hline 24}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHwhite c.threat2##treatment female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       625

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 624.658331
{txt}{col 1}Number of PSUs{col 19}= {res}      625
{txt}{col 49}Average RVI{col 67}= {res}    0.1300
{txt}{col 49}Largest FMI{col 67}= {res}    0.2611
{txt}{col 49}Complete DF{col 67}= {res}       624
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    109.93
{txt}{col 49}        avg{col 67}= {res}    357.00
{txt}{col 49}        max{col 67}= {res}    606.65
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  17{txt},{res}  589.1{txt}){col 67}= {res}      1.68
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0422

{txt}{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}                GHwhite{col 25}{c |}      Coef.{col 37}   Std. Err.{col 49}      t{col 57}   P>|t|{col 65}     [95% Con{col 78}f. Interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 16}threat2 {c |}{col 25}{res}{space 2} .1255357{col 37}{space 2}  .095672{col 48}{space 1}    1.31{col 57}{space 3}0.190{col 65}{space 4}-.0624849{col 78}{space 3} .3135563
{txt}{space 23} {c |}
{space 14}treatment {c |}
received coupled items  {c |}{col 25}{res}{space 2} .5333154{col 37}{space 2} .3760589{col 48}{space 1}    1.42{col 57}{space 3}0.157{col 65}{space 4}-.2063764{col 78}{space 3} 1.273007
{txt}{space 23} {c |}
{space 4}treatment#c.threat2 {c |}
received coupled items  {c |}{col 25}{res}{space 2}-.2138233{col 37}{space 2}  .131428{col 48}{space 1}   -1.63{col 57}{space 3}0.105{col 65}{space 4}-.4726901{col 78}{space 3} .0450434
{txt}{space 23} {c |}
{space 17}female {c |}{col 25}{res}{space 2} .2157561{col 37}{space 2} .1049047{col 48}{space 1}    2.06{col 57}{space 3}0.040{col 65}{space 4} .0097356{col 78}{space 3} .4217765
{txt}{space 20}Age {c |}{col 25}{res}{space 2}-.0155914{col 37}{space 2} .0057384{col 48}{space 1}   -2.72{col 57}{space 3}0.007{col 65}{space 4}-.0268732{col 78}{space 3}-.0043096
{txt}{space 16}edu_age {c |}{col 25}{res}{space 2}-.0169696{col 37}{space 2} .0346667{col 48}{space 1}   -0.49{col 57}{space 3}0.625{col 65}{space 4} -.085135{col 78}{space 3} .0511958
{txt}{space 23} {c |}
{space 12}SocialGrade {c |}
{space 20}C1  {c |}{col 25}{res}{space 2}-.0207918{col 37}{space 2} .1361648{col 48}{space 1}   -0.15{col 57}{space 3}0.879{col 65}{space 4}-.2885111{col 78}{space 3} .2469275
{txt}{space 20}C2  {c |}{col 25}{res}{space 2}-.0333256{col 37}{space 2} .1953372{col 48}{space 1}   -0.17{col 57}{space 3}0.865{col 65}{space 4}-.4171349{col 78}{space 3} .3504838
{txt}{space 20}DE  {c |}{col 25}{res}{space 2}-.0398957{col 37}{space 2} .1717238{col 48}{space 1}   -0.23{col 57}{space 3}0.816{col 65}{space 4}-.3772901{col 78}{space 3} .2974987
{txt}{space 23} {c |}
{space 12}work_status {c |}
{space 5}working part time  {c |}{col 25}{res}{space 2} .0133157{col 37}{space 2} .1514064{col 48}{space 1}    0.09{col 57}{space 3}0.930{col 65}{space 4}-.2841066{col 78}{space 3} .3107381
{txt}{space 5}full time student  {c |}{col 25}{res}{space 2} .1403075{col 37}{space 2} .3203466{col 48}{space 1}    0.44{col 57}{space 3}0.662{col 65}{space 4}-.4897348{col 78}{space 3} .7703498
{txt}{space 15}retired  {c |}{col 25}{res}{space 2}  .261445{col 37}{space 2} .1748934{col 48}{space 1}    1.49{col 57}{space 3}0.136{col 65}{space 4}-.0829185{col 78}{space 3} .6058085
{txt}{space 12}unemployed  {c |}{col 25}{res}{space 2}-.0067862{col 37}{space 2}  .262676{col 48}{space 1}   -0.03{col 57}{space 3}0.979{col 65}{space 4}-.5241039{col 78}{space 3} .5105315
{txt}{space 11}not working  {c |}{col 25}{res}{space 2} .3099133{col 37}{space 2} .2675952{col 48}{space 1}    1.16{col 57}{space 3}0.247{col 65}{space 4}-.2157559{col 78}{space 3} .8355826
{txt}{space 23} {c |}
{space 17}UKborn {c |}{col 25}{res}{space 2} .0342136{col 37}{space 2} .2443287{col 48}{space 1}    0.14{col 57}{space 3}0.889{col 65}{space 4}-.4499922{col 78}{space 3} .5184193
{txt}{space 13}authvalues {c |}{col 25}{res}{space 2} .2172411{col 37}{space 2} .1098903{col 48}{space 1}    1.98{col 57}{space 3}0.050{col 65}{space 4}-.0004146{col 78}{space 3} .4348968
{txt}{space 16}selfest {c |}{col 25}{res}{space 2} .1855946{col 37}{space 2} .2348704{col 48}{space 1}    0.79{col 57}{space 3}0.430{col 65}{space 4}-.2773551{col 78}{space 3} .6485442
{txt}{space 18}_cons {c |}{col 25}{res}{space 2} 2.227823{col 37}{space 2} .9705624{col 48}{space 1}    2.30{col 57}{space 3}0.022{col 65}{space 4} .3170324{col 78}{space 3} 4.138613
{txt}{hline 24}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHwhite c.threat3##treatment female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       628

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 628.153469
{txt}{col 1}Number of PSUs{col 19}= {res}      628
{txt}{col 49}Average RVI{col 67}= {res}    0.1290
{txt}{col 49}Largest FMI{col 67}= {res}    0.2405
{txt}{col 49}Complete DF{col 67}= {res}       627
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    124.92
{txt}{col 49}        avg{col 67}= {res}    353.06
{txt}{col 49}        max{col 67}= {res}    597.05
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  17{txt},{res}  591.9{txt}){col 67}= {res}      1.97
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0114

{txt}{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}                GHwhite{col 25}{c |}      Coef.{col 37}   Std. Err.{col 49}      t{col 57}   P>|t|{col 65}     [95% Con{col 78}f. Interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 16}threat3 {c |}{col 25}{res}{space 2} .2496604{col 37}{space 2} .0845158{col 48}{space 1}    2.95{col 57}{space 3}0.003{col 65}{space 4} .0834303{col 78}{space 3} .4158905
{txt}{space 23} {c |}
{space 14}treatment {c |}
received coupled items  {c |}{col 25}{res}{space 2} .8844198{col 37}{space 2}  .340596{col 48}{space 1}    2.60{col 57}{space 3}0.010{col 65}{space 4} .2142881{col 78}{space 3} 1.554552
{txt}{space 23} {c |}
{space 4}treatment#c.threat3 {c |}
received coupled items  {c |}{col 25}{res}{space 2}-.3259658{col 37}{space 2} .1163829{col 48}{space 1}   -2.80{col 57}{space 3}0.006{col 65}{space 4} -.555277{col 78}{space 3}-.0966546
{txt}{space 23} {c |}
{space 17}female {c |}{col 25}{res}{space 2} .1709696{col 37}{space 2} .1049831{col 48}{space 1}    1.63{col 57}{space 3}0.104{col 65}{space 4}-.0352114{col 78}{space 3} .3771507
{txt}{space 20}Age {c |}{col 25}{res}{space 2}-.0161944{col 37}{space 2} .0057873{col 48}{space 1}   -2.80{col 57}{space 3}0.005{col 65}{space 4} -.027571{col 78}{space 3}-.0048179
{txt}{space 16}edu_age {c |}{col 25}{res}{space 2} -.007023{col 37}{space 2} .0347453{col 48}{space 1}   -0.20{col 57}{space 3}0.840{col 65}{space 4}-.0753358{col 78}{space 3} .0612898
{txt}{space 23} {c |}
{space 12}SocialGrade {c |}
{space 20}C1  {c |}{col 25}{res}{space 2} .0073235{col 37}{space 2} .1334216{col 48}{space 1}    0.05{col 57}{space 3}0.956{col 65}{space 4} -.254985{col 78}{space 3} .2696321
{txt}{space 20}C2  {c |}{col 25}{res}{space 2}-.0949186{col 37}{space 2}   .17974{col 48}{space 1}   -0.53{col 57}{space 3}0.598{col 65}{space 4}-.4480965{col 78}{space 3} .2582593
{txt}{space 20}DE  {c |}{col 25}{res}{space 2}-.0403784{col 37}{space 2} .1751585{col 48}{space 1}   -0.23{col 57}{space 3}0.818{col 65}{space 4}-.3845357{col 78}{space 3}  .303779
{txt}{space 23} {c |}
{space 12}work_status {c |}
{space 5}working part time  {c |}{col 25}{res}{space 2} .0571119{col 37}{space 2} .1479513{col 48}{space 1}    0.39{col 57}{space 3}0.700{col 65}{space 4}-.2335469{col 78}{space 3} .3477707
{txt}{space 5}full time student  {c |}{col 25}{res}{space 2} .0476785{col 37}{space 2} .3076505{col 48}{space 1}    0.15{col 57}{space 3}0.877{col 65}{space 4}-.5577123{col 78}{space 3} .6530693
{txt}{space 15}retired  {c |}{col 25}{res}{space 2} .2725628{col 37}{space 2}  .177152{col 48}{space 1}    1.54{col 57}{space 3}0.125{col 65}{space 4} -.076146{col 78}{space 3} .6212715
{txt}{space 12}unemployed  {c |}{col 25}{res}{space 2}  .179561{col 37}{space 2} .2840507{col 48}{space 1}    0.63{col 57}{space 3}0.528{col 65}{space 4}-.3793217{col 78}{space 3} .7384436
{txt}{space 11}not working  {c |}{col 25}{res}{space 2} .3665293{col 37}{space 2} .2682458{col 48}{space 1}    1.37{col 57}{space 3}0.172{col 65}{space 4}-.1604218{col 78}{space 3} .8934804
{txt}{space 23} {c |}
{space 17}UKborn {c |}{col 25}{res}{space 2} .1221105{col 37}{space 2} .2433089{col 48}{space 1}    0.50{col 57}{space 3}0.617{col 65}{space 4} -.359431{col 78}{space 3}  .603652
{txt}{space 13}authvalues {c |}{col 25}{res}{space 2} .1904881{col 37}{space 2} .1090883{col 48}{space 1}    1.75{col 57}{space 3}0.083{col 65}{space 4}-.0252659{col 78}{space 3}  .406242
{txt}{space 16}selfest {c |}{col 25}{res}{space 2} .0927562{col 37}{space 2} .2312358{col 48}{space 1}    0.40{col 57}{space 3}0.689{col 65}{space 4}-.3632691{col 78}{space 3} .5487816
{txt}{space 18}_cons {c |}{col 25}{res}{space 2} 1.729238{col 37}{space 2} .9397216{col 48}{space 1}    1.84{col 57}{space 3}0.067{col 65}{space 4}-.1199259{col 78}{space 3} 3.578401
{txt}{hline 24}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHwhite c.threat4##treatment female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       627

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 627.168555
{txt}{col 1}Number of PSUs{col 19}= {res}      627
{txt}{col 49}Average RVI{col 67}= {res}    0.1280
{txt}{col 49}Largest FMI{col 67}= {res}    0.2350
{txt}{col 49}Complete DF{col 67}= {res}       626
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    129.32
{txt}{col 49}        avg{col 67}= {res}    380.64
{txt}{col 49}        max{col 67}= {res}    604.14
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  17{txt},{res}  591.1{txt}){col 67}= {res}      1.77
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0288

{txt}{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}                GHwhite{col 25}{c |}      Coef.{col 37}   Std. Err.{col 49}      t{col 57}   P>|t|{col 65}     [95% Con{col 78}f. Interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 16}threat4 {c |}{col 25}{res}{space 2} .1284407{col 37}{space 2} .0806319{col 48}{space 1}    1.59{col 57}{space 3}0.112{col 65}{space 4}-.0300918{col 78}{space 3} .2869732
{txt}{space 23} {c |}
{space 14}treatment {c |}
received coupled items  {c |}{col 25}{res}{space 2} .6988811{col 37}{space 2} .3529437{col 48}{space 1}    1.98{col 57}{space 3}0.048{col 65}{space 4} .0051626{col 78}{space 3}   1.3926
{txt}{space 23} {c |}
{space 4}treatment#c.threat4 {c |}
received coupled items  {c |}{col 25}{res}{space 2}-.2480271{col 37}{space 2} .1093404{col 48}{space 1}   -2.27{col 57}{space 3}0.024{col 65}{space 4}-.4630298{col 78}{space 3}-.0330244
{txt}{space 23} {c |}
{space 17}female {c |}{col 25}{res}{space 2} .2066076{col 37}{space 2} .1028229{col 48}{space 1}    2.01{col 57}{space 3}0.045{col 65}{space 4}  .004674{col 78}{space 3} .4085413
{txt}{space 20}Age {c |}{col 25}{res}{space 2}-.0160699{col 37}{space 2} .0057885{col 48}{space 1}   -2.78{col 57}{space 3}0.006{col 65}{space 4}-.0274497{col 78}{space 3}-.0046902
{txt}{space 16}edu_age {c |}{col 25}{res}{space 2}-.0132753{col 37}{space 2} .0344803{col 48}{space 1}   -0.39{col 57}{space 3}0.700{col 65}{space 4}-.0810363{col 78}{space 3} .0544857
{txt}{space 23} {c |}
{space 12}SocialGrade {c |}
{space 20}C1  {c |}{col 25}{res}{space 2}   .01205{col 37}{space 2} .1343175{col 48}{space 1}    0.09{col 57}{space 3}0.929{col 65}{space 4}-.2519896{col 78}{space 3} .2760896
{txt}{space 20}C2  {c |}{col 25}{res}{space 2}-.0584412{col 37}{space 2} .1835042{col 48}{space 1}   -0.32{col 57}{space 3}0.750{col 65}{space 4}-.4190232{col 78}{space 3} .3021407
{txt}{space 20}DE  {c |}{col 25}{res}{space 2}-.0161941{col 37}{space 2} .1747626{col 48}{space 1}   -0.09{col 57}{space 3}0.926{col 65}{space 4}-.3595862{col 78}{space 3}  .327198
{txt}{space 23} {c |}
{space 12}work_status {c |}
{space 5}working part time  {c |}{col 25}{res}{space 2} .0140327{col 37}{space 2}  .148011{col 48}{space 1}    0.09{col 57}{space 3}0.925{col 65}{space 4}-.2767267{col 78}{space 3} .3047922
{txt}{space 5}full time student  {c |}{col 25}{res}{space 2} .0655423{col 37}{space 2} .3043242{col 48}{space 1}    0.22{col 57}{space 3}0.830{col 65}{space 4}-.5333478{col 78}{space 3} .6644323
{txt}{space 15}retired  {c |}{col 25}{res}{space 2} .2692171{col 37}{space 2} .1767796{col 48}{space 1}    1.52{col 57}{space 3}0.129{col 65}{space 4}-.0787179{col 78}{space 3} .6171521
{txt}{space 12}unemployed  {c |}{col 25}{res}{space 2} .1252513{col 37}{space 2}  .287941{col 48}{space 1}    0.43{col 57}{space 3}0.664{col 65}{space 4}-.4412762{col 78}{space 3} .6917789
{txt}{space 11}not working  {c |}{col 25}{res}{space 2} .3410999{col 37}{space 2}  .267347{col 48}{space 1}    1.28{col 57}{space 3}0.203{col 65}{space 4}-.1840826{col 78}{space 3} .8662823
{txt}{space 23} {c |}
{space 17}UKborn {c |}{col 25}{res}{space 2} -.127779{col 37}{space 2} .2445154{col 48}{space 1}   -0.52{col 57}{space 3}0.602{col 65}{space 4}-.6111533{col 78}{space 3} .3555954
{txt}{space 13}authvalues {c |}{col 25}{res}{space 2} .2052757{col 37}{space 2} .1094539{col 48}{space 1}    1.88{col 57}{space 3}0.063{col 65}{space 4}-.0112764{col 78}{space 3} .4218278
{txt}{space 16}selfest {c |}{col 25}{res}{space 2} .1194815{col 37}{space 2} .2349242{col 48}{space 1}    0.51{col 57}{space 3}0.612{col 65}{space 4}-.3440023{col 78}{space 3} .5829653
{txt}{space 18}_cons {c |}{col 25}{res}{space 2} 2.352968{col 37}{space 2}  .894252{col 48}{space 1}    2.63{col 57}{space 3}0.009{col 65}{space 4}  .595227{col 78}{space 3} 4.110709
{txt}{hline 24}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHwhite c.threat5##treatment female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       629

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 629.711727
{txt}{col 1}Number of PSUs{col 19}= {res}      629
{txt}{col 49}Average RVI{col 67}= {res}    0.1297
{txt}{col 49}Largest FMI{col 67}= {res}    0.2594
{txt}{col 49}Complete DF{col 67}= {res}       628
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    111.23
{txt}{col 49}        avg{col 67}= {res}    354.84
{txt}{col 49}        max{col 67}= {res}    612.51
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  17{txt},{res}  592.1{txt}){col 67}= {res}      1.87
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0179

{txt}{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}                GHwhite{col 25}{c |}      Coef.{col 37}   Std. Err.{col 49}      t{col 57}   P>|t|{col 65}     [95% Con{col 78}f. Interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 16}threat5 {c |}{col 25}{res}{space 2} .1809354{col 37}{space 2} .0960496{col 48}{space 1}    1.88{col 57}{space 3}0.060{col 65}{space 4}-.0079168{col 78}{space 3} .3697876
{txt}{space 23} {c |}
{space 14}treatment {c |}
received coupled items  {c |}{col 25}{res}{space 2} .7257752{col 37}{space 2} .3932494{col 48}{space 1}    1.85{col 57}{space 3}0.066{col 65}{space 4}-.0484948{col 78}{space 3} 1.500045
{txt}{space 23} {c |}
{space 4}treatment#c.threat5 {c |}
received coupled items  {c |}{col 25}{res}{space 2}-.2605043{col 37}{space 2} .1275266{col 48}{space 1}   -2.04{col 57}{space 3}0.042{col 65}{space 4}-.5119008{col 78}{space 3}-.0091077
{txt}{space 23} {c |}
{space 17}female {c |}{col 25}{res}{space 2} .2222311{col 37}{space 2} .1038792{col 48}{space 1}    2.14{col 57}{space 3}0.033{col 65}{space 4} .0182286{col 78}{space 3} .4262336
{txt}{space 20}Age {c |}{col 25}{res}{space 2}-.0164996{col 37}{space 2} .0057493{col 48}{space 1}   -2.87{col 57}{space 3}0.004{col 65}{space 4}-.0278014{col 78}{space 3}-.0051977
{txt}{space 16}edu_age {c |}{col 25}{res}{space 2}-.0156768{col 37}{space 2} .0341119{col 48}{space 1}   -0.46{col 57}{space 3}0.646{col 65}{space 4}-.0827454{col 78}{space 3} .0513918
{txt}{space 23} {c |}
{space 12}SocialGrade {c |}
{space 20}C1  {c |}{col 25}{res}{space 2} .0026339{col 37}{space 2} .1327809{col 48}{space 1}    0.02{col 57}{space 3}0.984{col 65}{space 4}-.2584444{col 78}{space 3} .2637122
{txt}{space 20}C2  {c |}{col 25}{res}{space 2}-.0465978{col 37}{space 2} .1894854{col 48}{space 1}   -0.25{col 57}{space 3}0.806{col 65}{space 4}-.4188891{col 78}{space 3} .3256934
{txt}{space 20}DE  {c |}{col 25}{res}{space 2}-.0738668{col 37}{space 2} .1715316{col 48}{space 1}   -0.43{col 57}{space 3}0.667{col 65}{space 4} -.410891{col 78}{space 3} .2631575
{txt}{space 23} {c |}
{space 12}work_status {c |}
{space 5}working part time  {c |}{col 25}{res}{space 2} .0240237{col 37}{space 2} .1501291{col 48}{space 1}    0.16{col 57}{space 3}0.873{col 65}{space 4}-.2708821{col 78}{space 3} .3189295
{txt}{space 5}full time student  {c |}{col 25}{res}{space 2} .0011969{col 37}{space 2} .3076994{col 48}{space 1}    0.00{col 57}{space 3}0.997{col 65}{space 4}-.6042576{col 78}{space 3} .6066513
{txt}{space 15}retired  {c |}{col 25}{res}{space 2} .3176132{col 37}{space 2} .1746274{col 48}{space 1}    1.82{col 57}{space 3}0.070{col 65}{space 4}-.0259957{col 78}{space 3}  .661222
{txt}{space 12}unemployed  {c |}{col 25}{res}{space 2} .1247047{col 37}{space 2}  .287401{col 48}{space 1}    0.43{col 57}{space 3}0.665{col 65}{space 4}-.4406072{col 78}{space 3} .6900165
{txt}{space 11}not working  {c |}{col 25}{res}{space 2} .2977869{col 37}{space 2} .2661721{col 48}{space 1}    1.12{col 57}{space 3}0.264{col 65}{space 4}-.2250846{col 78}{space 3} .8206585
{txt}{space 23} {c |}
{space 17}UKborn {c |}{col 25}{res}{space 2} .0105978{col 37}{space 2} .2426491{col 48}{space 1}    0.04{col 57}{space 3}0.965{col 65}{space 4}-.4702168{col 78}{space 3} .4914124
{txt}{space 13}authvalues {c |}{col 25}{res}{space 2} .2089293{col 37}{space 2} .1093113{col 48}{space 1}    1.91{col 57}{space 3}0.058{col 65}{space 4}-.0074066{col 78}{space 3} .4252652
{txt}{space 16}selfest {c |}{col 25}{res}{space 2} .1989891{col 37}{space 2} .2289066{col 48}{space 1}    0.87{col 57}{space 3}0.386{col 65}{space 4}-.2520582{col 78}{space 3} .6500365
{txt}{space 18}_cons {c |}{col 25}{res}{space 2} 2.072096{col 37}{space 2} .9416855{col 48}{space 1}    2.20{col 57}{space 3}0.029{col 65}{space 4} .2176047{col 78}{space 3} 3.926588
{txt}{hline 24}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. 
. *********************************************************************
. * TABLE A.8A IN THE APPENDIX:
. *       Predictors of Group Hostility under Decoupled Condition, 2011; with Covariates Shown
. * FIGURE A.2 IN THE APPENDIX:
. *       Unstandardized OLS Coefficient Estimates and 95% Confidence Intervals of the Impact of  
. *       Threats on Group Hostility; Threats Entered Simultaneously (2011 estimates)
. **      NOTE: for significance test of difference between 2011 and 2016 estimates, 
. **      see code for FIGURE A.2 below 
. *********************************************************************
. 
. mi estimate: svy: reg GHblack threat1 threat2 threat3 threat4 threat5 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest if treatment==0 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       409

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 410.914422
{txt}{col 1}Number of PSUs{col 19}= {res}      409
{txt}{col 49}Average RVI{col 67}= {res}    0.1295
{txt}{col 49}Largest FMI{col 67}= {res}    0.3187
{txt}{col 49}Complete DF{col 67}= {res}       408
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}     72.58
{txt}{col 49}        avg{col 67}= {res}    243.84
{txt}{col 49}        max{col 67}= {res}    375.50
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  19{txt},{res}  393.3{txt}){col 67}= {res}     10.49
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           GHblack{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat1 {c |}{col 20}{res}{space 2} .0859609{col 32}{space 2} .0410717{col 43}{space 1}    2.09{col 52}{space 3}0.037{col 60}{space 4} .0051778{col 73}{space 3}  .166744
{txt}{space 11}threat2 {c |}{col 20}{res}{space 2}-.0238519{col 32}{space 2} .0528471{col 43}{space 1}   -0.45{col 52}{space 3}0.652{col 60}{space 4}-.1279093{col 73}{space 3} .0802055
{txt}{space 11}threat3 {c |}{col 20}{res}{space 2} .0102645{col 32}{space 2} .0419237{col 43}{space 1}    0.24{col 52}{space 3}0.807{col 60}{space 4}-.0722393{col 73}{space 3} .0927682
{txt}{space 11}threat4 {c |}{col 20}{res}{space 2} .1744879{col 32}{space 2} .0324962{col 43}{space 1}    5.37{col 52}{space 3}0.000{col 60}{space 4} .1103807{col 73}{space 3}  .238595
{txt}{space 11}threat5 {c |}{col 20}{res}{space 2}-.0243403{col 32}{space 2} .0456357{col 43}{space 1}   -0.53{col 52}{space 3}0.594{col 60}{space 4}-.1142077{col 73}{space 3}  .065527
{txt}{space 12}female {c |}{col 20}{res}{space 2}-.0795249{col 32}{space 2} .0538973{col 43}{space 1}   -1.48{col 52}{space 3}0.141{col 60}{space 4}-.1856227{col 73}{space 3} .0265729
{txt}{space 15}Age {c |}{col 20}{res}{space 2}-.0035349{col 32}{space 2} .0031775{col 43}{space 1}   -1.11{col 52}{space 3}0.267{col 60}{space 4}-.0098047{col 73}{space 3} .0027349
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0094593{col 32}{space 2} .0185798{col 43}{space 1}   -0.51{col 52}{space 3}0.612{col 60}{space 4}-.0464923{col 73}{space 3} .0275737
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2} -.022479{col 32}{space 2} .0647439{col 43}{space 1}   -0.35{col 52}{space 3}0.729{col 60}{space 4} -.149958{col 73}{space 3}     .105
{txt}{space 15}C2  {c |}{col 20}{res}{space 2}-.0093196{col 32}{space 2}  .091409{col 43}{space 1}   -0.10{col 52}{space 3}0.919{col 60}{space 4}-.1890792{col 73}{space 3}   .17044
{txt}{space 15}DE  {c |}{col 20}{res}{space 2}-.0692732{col 32}{space 2} .0917645{col 43}{space 1}   -0.75{col 52}{space 3}0.451{col 60}{space 4}-.2502909{col 73}{space 3} .1117446
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2}-.0997273{col 32}{space 2} .0865681{col 43}{space 1}   -1.15{col 52}{space 3}0.250{col 60}{space 4}-.2699992{col 73}{space 3} .0705447
{txt}full time student  {c |}{col 20}{res}{space 2}-.0527912{col 32}{space 2} .1364848{col 43}{space 1}   -0.39{col 52}{space 3}0.699{col 60}{space 4}-.3214269{col 73}{space 3} .2158444
{txt}{space 10}retired  {c |}{col 20}{res}{space 2} .1066397{col 32}{space 2} .0957087{col 43}{space 1}    1.11{col 52}{space 3}0.266{col 60}{space 4}-.0817727{col 73}{space 3} .2950521
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2} .2206656{col 32}{space 2} .2002256{col 43}{space 1}    1.10{col 52}{space 3}0.271{col 60}{space 4}-.1733435{col 73}{space 3} .6146747
{txt}{space 6}not working  {c |}{col 20}{res}{space 2} .0041243{col 32}{space 2} .1334497{col 43}{space 1}    0.03{col 52}{space 3}0.975{col 60}{space 4}-.2593584{col 73}{space 3}  .267607
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2}-.3998272{col 32}{space 2} .3516562{col 43}{space 1}   -1.14{col 52}{space 3}0.256{col 60}{space 4}-1.091289{col 73}{space 3}  .291635
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .3127817{col 32}{space 2} .0508724{col 43}{space 1}    6.15{col 52}{space 3}0.000{col 60}{space 4} .2122867{col 73}{space 3} .4132767
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .1728906{col 32}{space 2} .1165426{col 43}{space 1}    1.48{col 52}{space 3}0.140{col 60}{space 4}-.0577952{col 73}{space 3} .4035763
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 1.524819{col 32}{space 2} .5863776{col 43}{space 1}    2.60{col 52}{space 3}0.010{col 60}{space 4} .3663974{col 73}{space 3} 2.683241
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHMus threat1 threat2 threat3 threat4 threat5 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest if treatment==0 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       405

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 407.439681
{txt}{col 1}Number of PSUs{col 19}= {res}      405
{txt}{col 49}Average RVI{col 67}= {res}    0.1432
{txt}{col 49}Largest FMI{col 67}= {res}    0.2323
{txt}{col 49}Complete DF{col 67}= {res}       404
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    114.67
{txt}{col 49}        avg{col 67}= {res}    234.95
{txt}{col 49}        max{col 67}= {res}    383.43
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  19{txt},{res}  386.4{txt}){col 67}= {res}     11.66
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}             GHMus{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat1 {c |}{col 20}{res}{space 2} .0605185{col 32}{space 2} .0522981{col 43}{space 1}    1.16{col 52}{space 3}0.248{col 60}{space 4}-.0424583{col 73}{space 3} .1634953
{txt}{space 11}threat2 {c |}{col 20}{res}{space 2}  .013024{col 32}{space 2} .0576534{col 43}{space 1}    0.23{col 52}{space 3}0.822{col 60}{space 4}-.1010448{col 73}{space 3} .1270928
{txt}{space 11}threat3 {c |}{col 20}{res}{space 2} .0477734{col 32}{space 2} .0565146{col 43}{space 1}    0.85{col 52}{space 3}0.399{col 60}{space 4}-.0635249{col 73}{space 3} .1590716
{txt}{space 11}threat4 {c |}{col 20}{res}{space 2} .2787076{col 32}{space 2} .0382944{col 43}{space 1}    7.28{col 52}{space 3}0.000{col 60}{space 4} .2029707{col 73}{space 3} .3544445
{txt}{space 11}threat5 {c |}{col 20}{res}{space 2}-.0825042{col 32}{space 2} .0569595{col 43}{space 1}   -1.45{col 52}{space 3}0.149{col 60}{space 4}-.1949099{col 73}{space 3} .0299014
{txt}{space 12}female {c |}{col 20}{res}{space 2}-.0618831{col 32}{space 2} .0671902{col 43}{space 1}   -0.92{col 52}{space 3}0.358{col 60}{space 4}-.1942334{col 73}{space 3} .0704673
{txt}{space 15}Age {c |}{col 20}{res}{space 2}-.0041157{col 32}{space 2} .0031575{col 43}{space 1}   -1.30{col 52}{space 3}0.193{col 60}{space 4}-.0103277{col 73}{space 3} .0020963
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0384386{col 32}{space 2} .0199011{col 43}{space 1}   -1.93{col 52}{space 3}0.055{col 60}{space 4}-.0776857{col 73}{space 3} .0008085
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2}-.2159594{col 32}{space 2} .0761021{col 43}{space 1}   -2.84{col 52}{space 3}0.005{col 60}{space 4}-.3657333{col 73}{space 3}-.0661854
{txt}{space 15}C2  {c |}{col 20}{res}{space 2}-.0252086{col 32}{space 2} .0967638{col 43}{space 1}   -0.26{col 52}{space 3}0.795{col 60}{space 4}-.2156413{col 73}{space 3} .1652242
{txt}{space 15}DE  {c |}{col 20}{res}{space 2}-.1288988{col 32}{space 2} .1069548{col 43}{space 1}   -1.21{col 52}{space 3}0.229{col 60}{space 4}-.3396788{col 73}{space 3} .0818811
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2}-.1070001{col 32}{space 2} .0968429{col 43}{space 1}   -1.10{col 52}{space 3}0.270{col 60}{space 4} -.297603{col 73}{space 3} .0836028
{txt}full time student  {c |}{col 20}{res}{space 2} .0472455{col 32}{space 2} .2107374{col 43}{space 1}    0.22{col 52}{space 3}0.823{col 60}{space 4}-.3678421{col 73}{space 3} .4623331
{txt}{space 10}retired  {c |}{col 20}{res}{space 2} .0912754{col 32}{space 2} .1035062{col 43}{space 1}    0.88{col 52}{space 3}0.379{col 60}{space 4}-.1124162{col 73}{space 3}  .294967
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2} .0415759{col 32}{space 2} .1957982{col 43}{space 1}    0.21{col 52}{space 3}0.832{col 60}{space 4}-.3441609{col 73}{space 3} .4273127
{txt}{space 6}not working  {c |}{col 20}{res}{space 2}-.0278512{col 32}{space 2} .1358082{col 43}{space 1}   -0.21{col 52}{space 3}0.838{col 60}{space 4}-.2962954{col 73}{space 3} .2405931
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2}-.1434088{col 32}{space 2} .5939582{col 43}{space 1}   -0.24{col 52}{space 3}0.809{col 60}{space 4}-1.311232{col 73}{space 3} 1.024414
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .1775621{col 32}{space 2} .0582565{col 43}{space 1}    3.05{col 52}{space 3}0.003{col 60}{space 4} .0625207{col 73}{space 3} .2926036
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .2947539{col 32}{space 2} .1332674{col 43}{space 1}    2.21{col 52}{space 3}0.029{col 60}{space 4} .0307686{col 73}{space 3} .5587391
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 2.001151{col 32}{space 2} .7530883{col 43}{space 1}    2.66{col 52}{space 3}0.008{col 60}{space 4} .5190765{col 73}{space 3} 3.483226
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHEEur threat1 threat2 threat3 threat4 threat5 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest if treatment==0
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       404

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res}  406.50712
{txt}{col 1}Number of PSUs{col 19}= {res}      404
{txt}{col 49}Average RVI{col 67}= {res}    0.2066
{txt}{col 49}Largest FMI{col 67}= {res}    0.3744
{txt}{col 49}Complete DF{col 67}= {res}       403
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}     55.81
{txt}{col 49}        avg{col 67}= {res}    197.21
{txt}{col 49}        max{col 67}= {res}    325.95
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  19{txt},{res}  371.8{txt}){col 67}= {res}     12.65
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}            GHEEur{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat1 {c |}{col 20}{res}{space 2}  .001476{col 32}{space 2} .0435333{col 43}{space 1}    0.03{col 52}{space 3}0.973{col 60}{space 4}-.0844847{col 73}{space 3} .0874366
{txt}{space 11}threat2 {c |}{col 20}{res}{space 2}-.0082988{col 32}{space 2} .0517012{col 43}{space 1}   -0.16{col 52}{space 3}0.873{col 60}{space 4}-.1113811{col 73}{space 3} .0947834
{txt}{space 11}threat3 {c |}{col 20}{res}{space 2} .0871651{col 32}{space 2} .0429424{col 43}{space 1}    2.03{col 52}{space 3}0.043{col 60}{space 4} .0026313{col 73}{space 3}  .171699
{txt}{space 11}threat4 {c |}{col 20}{res}{space 2} .1690109{col 32}{space 2} .0347753{col 43}{space 1}    4.86{col 52}{space 3}0.000{col 60}{space 4} .1004422{col 73}{space 3} .2375796
{txt}{space 11}threat5 {c |}{col 20}{res}{space 2}-.0090078{col 32}{space 2} .0423013{col 43}{space 1}   -0.21{col 52}{space 3}0.832{col 60}{space 4}-.0926572{col 73}{space 3} .0746416
{txt}{space 12}female {c |}{col 20}{res}{space 2}-.0508989{col 32}{space 2} .0586218{col 43}{space 1}   -0.87{col 52}{space 3}0.386{col 60}{space 4}-.1665189{col 73}{space 3} .0647211
{txt}{space 15}Age {c |}{col 20}{res}{space 2}-.0048152{col 32}{space 2}  .002995{col 43}{space 1}   -1.61{col 52}{space 3}0.109{col 60}{space 4}-.0107071{col 73}{space 3} .0010767
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0533055{col 32}{space 2} .0176979{col 43}{space 1}   -3.01{col 52}{space 3}0.003{col 60}{space 4}-.0882102{col 73}{space 3}-.0184008
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2}-.0863461{col 32}{space 2} .0643065{col 43}{space 1}   -1.34{col 52}{space 3}0.181{col 60}{space 4}-.2129781{col 73}{space 3} .0402859
{txt}{space 15}C2  {c |}{col 20}{res}{space 2}  .049376{col 32}{space 2} .0973389{col 43}{space 1}    0.51{col 52}{space 3}0.612{col 60}{space 4}-.1422943{col 73}{space 3} .2410463
{txt}{space 15}DE  {c |}{col 20}{res}{space 2}-.0554229{col 32}{space 2} .0917444{col 43}{space 1}   -0.60{col 52}{space 3}0.546{col 60}{space 4}  -.23599{col 73}{space 3} .1251443
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2}-.1138563{col 32}{space 2} .0927645{col 43}{space 1}   -1.23{col 52}{space 3}0.222{col 60}{space 4}-.2972141{col 73}{space 3} .0695015
{txt}full time student  {c |}{col 20}{res}{space 2} -.152126{col 32}{space 2} .2034416{col 43}{space 1}   -0.75{col 52}{space 3}0.458{col 60}{space 4}-.5591856{col 73}{space 3} .2549336
{txt}{space 10}retired  {c |}{col 20}{res}{space 2}  .102604{col 32}{space 2} .0945352{col 43}{space 1}    1.09{col 52}{space 3}0.279{col 60}{space 4}-.0833779{col 73}{space 3} .2885858
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2}-.0011267{col 32}{space 2} .2114165{col 43}{space 1}   -0.01{col 52}{space 3}0.996{col 60}{space 4}-.4171728{col 73}{space 3} .4149194
{txt}{space 6}not working  {c |}{col 20}{res}{space 2}  .012962{col 32}{space 2} .1440431{col 43}{space 1}    0.09{col 52}{space 3}0.928{col 60}{space 4}-.2719566{col 73}{space 3} .2978806
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2}-.4285257{col 32}{space 2} .1330922{col 43}{space 1}   -3.22{col 52}{space 3}0.001{col 60}{space 4}-.6908327{col 73}{space 3}-.1662187
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .1603879{col 32}{space 2} .0595741{col 43}{space 1}    2.69{col 52}{space 3}0.009{col 60}{space 4} .0410379{col 73}{space 3} .2797378
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .1925602{col 32}{space 2} .1202417{col 43}{space 1}    1.60{col 52}{space 3}0.112{col 60}{space 4}-.0453978{col 73}{space 3} .4305183
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 2.671749{col 32}{space 2} .4956168{col 43}{space 1}    5.39{col 52}{space 3}0.000{col 60}{space 4} 1.694724{col 73}{space 3} 3.648774
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHwhite threat1 threat2 threat3 threat4 threat5 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest if treatment==0
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       395

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 398.484388
{txt}{col 1}Number of PSUs{col 19}= {res}      395
{txt}{col 49}Average RVI{col 67}= {res}    0.1355
{txt}{col 49}Largest FMI{col 67}= {res}    0.2109
{txt}{col 49}Complete DF{col 67}= {res}       394
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    128.70
{txt}{col 49}        avg{col 67}= {res}    274.56
{txt}{col 49}        max{col 67}= {res}    360.81
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  19{txt},{res}  379.2{txt}){col 67}= {res}      2.05
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0060

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           GHwhite{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat1 {c |}{col 20}{res}{space 2} .0689058{col 32}{space 2} .1072397{col 43}{space 1}    0.64{col 52}{space 3}0.521{col 60}{space 4}-.1420337{col 73}{space 3} .2798454
{txt}{space 11}threat2 {c |}{col 20}{res}{space 2}-.0731835{col 32}{space 2} .1157375{col 43}{space 1}   -0.63{col 52}{space 3}0.528{col 60}{space 4}-.3009277{col 73}{space 3} .1545606
{txt}{space 11}threat3 {c |}{col 20}{res}{space 2} .1586729{col 32}{space 2} .1124717{col 43}{space 1}    1.41{col 52}{space 3}0.160{col 60}{space 4}-.0628101{col 73}{space 3} .3801559
{txt}{space 11}threat4 {c |}{col 20}{res}{space 2} .0454654{col 32}{space 2}  .090936{col 43}{space 1}    0.50{col 52}{space 3}0.617{col 60}{space 4}-.1335616{col 73}{space 3} .2244923
{txt}{space 11}threat5 {c |}{col 20}{res}{space 2} .1086055{col 32}{space 2} .1126276{col 43}{space 1}    0.96{col 52}{space 3}0.336{col 60}{space 4}-.1132695{col 73}{space 3} .3304804
{txt}{space 12}female {c |}{col 20}{res}{space 2} .2348873{col 32}{space 2}   .13765{col 43}{space 1}    1.71{col 52}{space 3}0.089{col 60}{space 4}-.0358362{col 73}{space 3} .5056107
{txt}{space 15}Age {c |}{col 20}{res}{space 2}-.0147505{col 32}{space 2} .0072001{col 43}{space 1}   -2.05{col 52}{space 3}0.041{col 60}{space 4}-.0289161{col 73}{space 3} -.000585
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0145692{col 32}{space 2} .0467404{col 43}{space 1}   -0.31{col 52}{space 3}0.755{col 60}{space 4}-.1065366{col 73}{space 3} .0773981
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2} -.042237{col 32}{space 2} .1652175{col 43}{space 1}   -0.26{col 52}{space 3}0.798{col 60}{space 4}-.3672683{col 73}{space 3} .2827944
{txt}{space 15}C2  {c |}{col 20}{res}{space 2}-.0369763{col 32}{space 2} .2500939{col 43}{space 1}   -0.15{col 52}{space 3}0.883{col 60}{space 4}-.5292367{col 73}{space 3} .4552841
{txt}{space 15}DE  {c |}{col 20}{res}{space 2} .0362566{col 32}{space 2} .2398349{col 43}{space 1}    0.15{col 52}{space 3}0.880{col 60}{space 4}-.4358204{col 73}{space 3} .5083336
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2}-.1024274{col 32}{space 2} .1724506{col 43}{space 1}   -0.59{col 52}{space 3}0.553{col 60}{space 4} -.441562{col 73}{space 3} .2367072
{txt}full time student  {c |}{col 20}{res}{space 2} .6611363{col 32}{space 2} .3928558{col 43}{space 1}    1.68{col 52}{space 3}0.094{col 60}{space 4}-.1138237{col 73}{space 3} 1.436096
{txt}{space 10}retired  {c |}{col 20}{res}{space 2} .2560142{col 32}{space 2} .2288225{col 43}{space 1}    1.12{col 52}{space 3}0.264{col 60}{space 4}-.1942693{col 73}{space 3} .7062977
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2} .1745708{col 32}{space 2} .2334274{col 43}{space 1}    0.75{col 52}{space 3}0.455{col 60}{space 4}-.2857348{col 73}{space 3} .6348764
{txt}{space 6}not working  {c |}{col 20}{res}{space 2}  .420631{col 32}{space 2} .3463967{col 43}{space 1}    1.21{col 52}{space 3}0.225{col 60}{space 4}-.2607249{col 73}{space 3} 1.101987
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2}-.0227556{col 32}{space 2}  .397523{col 43}{space 1}   -0.06{col 52}{space 3}0.954{col 60}{space 4} -.809282{col 73}{space 3} .7637709
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .2368842{col 32}{space 2} .1397772{col 43}{space 1}    1.69{col 52}{space 3}0.092{col 60}{space 4}-.0389538{col 73}{space 3} .5127222
{txt}{space 11}selfest {c |}{col 20}{res}{space 2}-.0464388{col 32}{space 2}  .277639{col 43}{space 1}   -0.17{col 52}{space 3}0.867{col 60}{space 4}-.5936146{col 73}{space 3}  .500737
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 1.651701{col 32}{space 2} 1.299355{col 43}{space 1}    1.27{col 52}{space 3}0.205{col 60}{space 4}-.9057734{col 73}{space 3} 4.209175
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. 
. *********************************************************************
. * TABLE A.9A IN THE APPENDIX:
. *       Predictors of Group Hostility under Decoupled Condition, 2011; with Hostility Toward White British
. * FIGURE 2 IN THE PAPER (2011 estimates):
. *       Unstandardized OLS Coefficient Estimates and 95% Confidence Intervals of the Impact of Threats
. *       on Group Hostility; Threats Entered Simultaneaously and with Hostility Toward White British
. **      NOTE: for significance test of difference between 2011 and 2016 estimates, 
. **      see code for FIGURE 2 below 
. *********************************************************************
. 
. mi estimate: svy: reg GHblack GHwhite threat1 threat2 threat3 threat4 threat5 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest if treatment==0 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       383

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res}  385.95058
{txt}{col 1}Number of PSUs{col 19}= {res}      383
{txt}{col 49}Average RVI{col 67}= {res}    0.2121
{txt}{col 49}Largest FMI{col 67}= {res}    0.6435
{txt}{col 49}Complete DF{col 67}= {res}       382
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}     20.62
{txt}{col 49}        avg{col 67}= {res}    215.09
{txt}{col 49}        max{col 67}= {res}    332.53
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  20{txt},{res}  354.2{txt}){col 67}= {res}      8.63
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           GHblack{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}GHwhite {c |}{col 20}{res}{space 2} .0915893{col 32}{space 2} .0420123{col 43}{space 1}    2.18{col 52}{space 3}0.041{col 60}{space 4} .0041228{col 73}{space 3} .1790557
{txt}{space 11}threat1 {c |}{col 20}{res}{space 2} .0931242{col 32}{space 2} .0441536{col 43}{space 1}    2.11{col 52}{space 3}0.036{col 60}{space 4} .0062356{col 73}{space 3} .1800128
{txt}{space 11}threat2 {c |}{col 20}{res}{space 2} -.028872{col 32}{space 2} .0536764{col 43}{space 1}   -0.54{col 52}{space 3}0.591{col 60}{space 4}-.1345737{col 73}{space 3} .0768296
{txt}{space 11}threat3 {c |}{col 20}{res}{space 2} .0035125{col 32}{space 2} .0450737{col 43}{space 1}    0.08{col 52}{space 3}0.938{col 60}{space 4}-.0852746{col 73}{space 3} .0922996
{txt}{space 11}threat4 {c |}{col 20}{res}{space 2} .1601322{col 32}{space 2} .0350183{col 43}{space 1}    4.57{col 52}{space 3}0.000{col 60}{space 4} .0909801{col 73}{space 3} .2292843
{txt}{space 11}threat5 {c |}{col 20}{res}{space 2}-.0427327{col 32}{space 2}  .044155{col 43}{space 1}   -0.97{col 52}{space 3}0.334{col 60}{space 4}-.1296514{col 73}{space 3} .0441861
{txt}{space 12}female {c |}{col 20}{res}{space 2}-.1157036{col 32}{space 2}  .055497{col 43}{space 1}   -2.08{col 52}{space 3}0.038{col 60}{space 4}-.2250391{col 73}{space 3} -.006368
{txt}{space 15}Age {c |}{col 20}{res}{space 2}-.0020958{col 32}{space 2} .0030241{col 43}{space 1}   -0.69{col 52}{space 3}0.489{col 60}{space 4}-.0080626{col 73}{space 3}  .003871
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2} .0010711{col 32}{space 2} .0181376{col 43}{space 1}    0.06{col 52}{space 3}0.953{col 60}{space 4}-.0351674{col 73}{space 3} .0373096
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2}-.0157539{col 32}{space 2} .0666478{col 43}{space 1}   -0.24{col 52}{space 3}0.813{col 60}{space 4}-.1470296{col 73}{space 3} .1155219
{txt}{space 15}C2  {c |}{col 20}{res}{space 2} .0152373{col 32}{space 2} .0894352{col 43}{space 1}    0.17{col 52}{space 3}0.865{col 60}{space 4}-.1606928{col 73}{space 3} .1911674
{txt}{space 15}DE  {c |}{col 20}{res}{space 2}-.0132995{col 32}{space 2} .0930233{col 43}{space 1}   -0.14{col 52}{space 3}0.886{col 60}{space 4}-.1968253{col 73}{space 3} .1702262
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2}-.1157985{col 32}{space 2} .0863755{col 43}{space 1}   -1.34{col 52}{space 3}0.181{col 60}{space 4}-.2857469{col 73}{space 3}   .05415
{txt}full time student  {c |}{col 20}{res}{space 2}-.1089462{col 32}{space 2} .1544261{col 43}{space 1}   -0.71{col 52}{space 3}0.481{col 60}{space 4}-.4130879{col 73}{space 3} .1951955
{txt}{space 10}retired  {c |}{col 20}{res}{space 2} .0952737{col 32}{space 2} .0966574{col 43}{space 1}    0.99{col 52}{space 3}0.325{col 60}{space 4}-.0950352{col 73}{space 3} .2855826
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2} .1850532{col 32}{space 2}  .202631{col 43}{space 1}    0.91{col 52}{space 3}0.362{col 60}{space 4}-.2138909{col 73}{space 3} .5839972
{txt}{space 6}not working  {c |}{col 20}{res}{space 2}-.0325324{col 32}{space 2} .1216091{col 43}{space 1}   -0.27{col 52}{space 3}0.789{col 60}{space 4} -.273099{col 73}{space 3} .2080342
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2}-.3448133{col 32}{space 2} .3302688{col 43}{space 1}   -1.04{col 52}{space 3}0.297{col 60}{space 4}-.9945016{col 73}{space 3} .3048749
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .2881008{col 32}{space 2} .0499265{col 43}{space 1}    5.77{col 52}{space 3}0.000{col 60}{space 4} .1895546{col 73}{space 3}  .386647
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .1506852{col 32}{space 2}   .11944{col 43}{space 1}    1.26{col 52}{space 3}0.209{col 60}{space 4}-.0856552{col 73}{space 3} .3870256
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 1.214235{col 32}{space 2} .5574361{col 43}{space 1}    2.18{col 52}{space 3}0.031{col 60}{space 4} .1128168{col 73}{space 3} 2.315653
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHMus GHwhite threat1 threat2 threat3 threat4 threat5 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest if treatment==0 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       380

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res}  382.95058
{txt}{col 1}Number of PSUs{col 19}= {res}      380
{txt}{col 49}Average RVI{col 67}= {res}    0.2000
{txt}{col 49}Largest FMI{col 67}= {res}    0.5465
{txt}{col 49}Complete DF{col 67}= {res}       379
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}     28.31
{txt}{col 49}        avg{col 67}= {res}    208.96
{txt}{col 49}        max{col 67}= {res}    354.46
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  20{txt},{res}  353.6{txt}){col 67}= {res}     10.34
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}             GHMus{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}GHwhite {c |}{col 20}{res}{space 2} .0733133{col 32}{space 2} .0398261{col 43}{space 1}    1.84{col 52}{space 3}0.076{col 60}{space 4}-.0082266{col 73}{space 3} .1548532
{txt}{space 11}threat1 {c |}{col 20}{res}{space 2} .0467731{col 32}{space 2} .0542704{col 43}{space 1}    0.86{col 52}{space 3}0.390{col 60}{space 4}-.0602009{col 73}{space 3}  .153747
{txt}{space 11}threat2 {c |}{col 20}{res}{space 2} .0079859{col 32}{space 2} .0578503{col 43}{space 1}    0.14{col 52}{space 3}0.890{col 60}{space 4}-.1065657{col 73}{space 3} .1225374
{txt}{space 11}threat3 {c |}{col 20}{res}{space 2} .0528585{col 32}{space 2} .0579981{col 43}{space 1}    0.91{col 52}{space 3}0.363{col 60}{space 4}-.0614998{col 73}{space 3} .1672168
{txt}{space 11}threat4 {c |}{col 20}{res}{space 2} .2817762{col 32}{space 2} .0401248{col 43}{space 1}    7.02{col 52}{space 3}0.000{col 60}{space 4} .2023372{col 73}{space 3} .3612153
{txt}{space 11}threat5 {c |}{col 20}{res}{space 2} -.091037{col 32}{space 2}  .057773{col 43}{space 1}   -1.58{col 52}{space 3}0.117{col 60}{space 4}-.2050708{col 73}{space 3} .0229968
{txt}{space 12}female {c |}{col 20}{res}{space 2}-.0850209{col 32}{space 2} .0672606{col 43}{space 1}   -1.26{col 52}{space 3}0.207{col 60}{space 4}-.2175144{col 73}{space 3} .0474726
{txt}{space 15}Age {c |}{col 20}{res}{space 2} -.002674{col 32}{space 2} .0031507{col 43}{space 1}   -0.85{col 52}{space 3}0.397{col 60}{space 4}-.0088754{col 73}{space 3} .0035273
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0268057{col 32}{space 2} .0196985{col 43}{space 1}   -1.36{col 52}{space 3}0.175{col 60}{space 4}-.0656399{col 73}{space 3} .0120285
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2}-.2418376{col 32}{space 2} .0763858{col 43}{space 1}   -3.17{col 52}{space 3}0.002{col 60}{space 4}-.3922118{col 73}{space 3}-.0914635
{txt}{space 15}C2  {c |}{col 20}{res}{space 2}-.0174004{col 32}{space 2} .0969576{col 43}{space 1}   -0.18{col 52}{space 3}0.858{col 60}{space 4} -.208229{col 73}{space 3} .1734282
{txt}{space 15}DE  {c |}{col 20}{res}{space 2}-.0808039{col 32}{space 2} .1080319{col 43}{space 1}   -0.75{col 52}{space 3}0.455{col 60}{space 4}-.2937045{col 73}{space 3} .1320966
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2}-.1209756{col 32}{space 2} .0971621{col 43}{space 1}   -1.25{col 52}{space 3}0.214{col 60}{space 4}-.3122414{col 73}{space 3} .0702902
{txt}full time student  {c |}{col 20}{res}{space 2} .1307085{col 32}{space 2} .2254669{col 43}{space 1}    0.58{col 52}{space 3}0.563{col 60}{space 4}-.3135216{col 73}{space 3} .5749386
{txt}{space 10}retired  {c |}{col 20}{res}{space 2} .0864869{col 32}{space 2} .1058818{col 43}{space 1}    0.82{col 52}{space 3}0.415{col 60}{space 4}-.1220026{col 73}{space 3} .2949764
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2} .0256216{col 32}{space 2}  .193191{col 43}{space 1}    0.13{col 52}{space 3}0.895{col 60}{space 4}-.3552617{col 73}{space 3} .4065049
{txt}{space 6}not working  {c |}{col 20}{res}{space 2}-.0237102{col 32}{space 2} .1348875{col 43}{space 1}   -0.18{col 52}{space 3}0.861{col 60}{space 4}-.2910731{col 73}{space 3} .2436527
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2}-.0932146{col 32}{space 2} .5646684{col 43}{space 1}   -0.17{col 52}{space 3}0.869{col 60}{space 4}-1.203736{col 73}{space 3} 1.017307
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .1625001{col 32}{space 2} .0580061{col 43}{space 1}    2.80{col 52}{space 3}0.006{col 60}{space 4} .0479488{col 73}{space 3} .2770514
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .2538348{col 32}{space 2} .1340722{col 43}{space 1}    1.89{col 52}{space 3}0.061{col 60}{space 4}-.0117263{col 73}{space 3} .5193959
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 1.627214{col 32}{space 2} .7342185{col 43}{space 1}    2.22{col 52}{space 3}0.027{col 60}{space 4} .1821674{col 73}{space 3} 3.072261
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHEEur GHwhite threat1 threat2 threat3 threat4 threat5 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest if treatment==0
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       381

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res}  383.95058
{txt}{col 1}Number of PSUs{col 19}= {res}      381
{txt}{col 49}Average RVI{col 67}= {res}    0.2514
{txt}{col 49}Largest FMI{col 67}= {res}    0.4310
{txt}{col 49}Complete DF{col 67}= {res}       380
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}     43.44
{txt}{col 49}        avg{col 67}= {res}    171.46
{txt}{col 49}        max{col 67}= {res}    314.53
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  20{txt},{res}  345.0{txt}){col 67}= {res}      8.01
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}            GHEEur{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}GHwhite {c |}{col 20}{res}{space 2} .0699665{col 32}{space 2} .0359198{col 43}{space 1}    1.95{col 52}{space 3}0.058{col 60}{space 4}-.0024514{col 73}{space 3} .1423844
{txt}{space 11}threat1 {c |}{col 20}{res}{space 2} .0023991{col 32}{space 2} .0461429{col 43}{space 1}    0.05{col 52}{space 3}0.959{col 60}{space 4}-.0888587{col 73}{space 3} .0936569
{txt}{space 11}threat2 {c |}{col 20}{res}{space 2}-.0019248{col 32}{space 2} .0526388{col 43}{space 1}   -0.04{col 52}{space 3}0.971{col 60}{space 4}-.1069831{col 73}{space 3} .1031335
{txt}{space 11}threat3 {c |}{col 20}{res}{space 2} .0711302{col 32}{space 2} .0458891{col 43}{space 1}    1.55{col 52}{space 3}0.123{col 60}{space 4}-.0193325{col 73}{space 3} .1615928
{txt}{space 11}threat4 {c |}{col 20}{res}{space 2} .1500684{col 32}{space 2} .0368581{col 43}{space 1}    4.07{col 52}{space 3}0.000{col 60}{space 4} .0773144{col 73}{space 3} .2228224
{txt}{space 11}threat5 {c |}{col 20}{res}{space 2}-.0189427{col 32}{space 2} .0423463{col 43}{space 1}   -0.45{col 52}{space 3}0.655{col 60}{space 4} -.102759{col 73}{space 3} .0648735
{txt}{space 12}female {c |}{col 20}{res}{space 2}-.0757832{col 32}{space 2} .0597835{col 43}{space 1}   -1.27{col 52}{space 3}0.206{col 60}{space 4}-.1936368{col 73}{space 3} .0420704
{txt}{space 15}Age {c |}{col 20}{res}{space 2}-.0042278{col 32}{space 2}  .002895{col 43}{space 1}   -1.46{col 52}{space 3}0.145{col 60}{space 4}-.0099261{col 73}{space 3} .0014705
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0507506{col 32}{space 2} .0177154{col 43}{space 1}   -2.86{col 52}{space 3}0.005{col 60}{space 4}-.0857133{col 73}{space 3} -.015788
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2}-.0784247{col 32}{space 2} .0667859{col 43}{space 1}   -1.17{col 52}{space 3}0.241{col 60}{space 4}-.2099911{col 73}{space 3} .0531418
{txt}{space 15}C2  {c |}{col 20}{res}{space 2} .0745692{col 32}{space 2} .0987296{col 43}{space 1}    0.76{col 52}{space 3}0.451{col 60}{space 4}-.1200234{col 73}{space 3} .2691618
{txt}{space 15}DE  {c |}{col 20}{res}{space 2}-.0528251{col 32}{space 2} .0946947{col 43}{space 1}   -0.56{col 52}{space 3}0.577{col 60}{space 4}-.2392593{col 73}{space 3}  .133609
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2}-.1366923{col 32}{space 2} .0930207{col 43}{space 1}   -1.47{col 52}{space 3}0.144{col 60}{space 4}-.3205811{col 73}{space 3} .0471966
{txt}full time student  {c |}{col 20}{res}{space 2}-.2053187{col 32}{space 2} .2195304{col 43}{space 1}   -0.94{col 52}{space 3}0.353{col 60}{space 4}-.6440758{col 73}{space 3} .2334384
{txt}{space 10}retired  {c |}{col 20}{res}{space 2} .1065503{col 32}{space 2} .0960067{col 43}{space 1}    1.11{col 52}{space 3}0.268{col 60}{space 4}-.0823461{col 73}{space 3} .2954468
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2}-.0300292{col 32}{space 2}  .214242{col 43}{space 1}   -0.14{col 52}{space 3}0.889{col 60}{space 4}-.4519308{col 73}{space 3} .3918725
{txt}{space 6}not working  {c |}{col 20}{res}{space 2}-.0110259{col 32}{space 2} .1375611{col 43}{space 1}   -0.08{col 52}{space 3}0.936{col 60}{space 4}-.2837304{col 73}{space 3} .2616787
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2}-.4010394{col 32}{space 2} .1360136{col 43}{space 1}   -2.95{col 52}{space 3}0.004{col 60}{space 4} -.669115{col 73}{space 3}-.1329638
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .1405109{col 32}{space 2} .0576491{col 43}{space 1}    2.44{col 52}{space 3}0.018{col 60}{space 4} .0252251{col 73}{space 3} .2557966
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .1854599{col 32}{space 2} .1240187{col 43}{space 1}    1.50{col 52}{space 3}0.137{col 60}{space 4}-.0600306{col 73}{space 3} .4309503
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 2.595388{col 32}{space 2} .5014902{col 43}{space 1}    5.18{col 52}{space 3}0.000{col 60}{space 4} 1.605564{col 73}{space 3} 3.585212
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. 
. *****************************************************************************************************************
. *   2016 analysis       
. *****************************************************************************************************************
. 
. * open data (from folder set as working directory):
. use "De Rooij et al. 2017 PSRM replication_2016.dta" , clear
{txt}( )

{com}. 
. 
. *********************************************************************
. * RECODES
. *********************************************************************
. 
. * threat1
. recode Q1a (5=.) (1=4 "strongly agree") (4=1 "strongly disagree") (2=3 "tend to agree") (3=2 "tend to disagree"), gen(threat1)
{txt}(1688 differences between Q1a and threat1)

{com}. * threat2
. recode Q1b (5=.) (1=4 "strongly agree") (4=1 "strongly disagree") (2=3 "tend to agree") (3=2 "tend to disagree"), gen(threat2)
{txt}(1688 differences between Q1b and threat2)

{com}. * threat3
. recode Q1c (5=.) (1=4 "strongly agree") (4=1 "strongly disagree") (2=3 "tend to agree") (3=2 "tend to disagree"), gen(threat3)
{txt}(1688 differences between Q1c and threat3)

{com}. * threat4
. recode Q1d (5=.) (1=4 "strongly agree") (4=1 "strongly disagree") (2=3 "tend to agree") (3=2 "tend to disagree"), gen(threat4)
{txt}(1688 differences between Q1d and threat4)

{com}. * threat5
. recode Q1e (5=.) (1=4 "strongly agree") (4=1 "strongly disagree") (2=3 "tend to agree") (3=2 "tend to disagree"), gen(threat5)
{txt}(1688 differences between Q1e and threat5)

{com}. * threat6
. recode Q1f (5=.) (1=1 "strongly agree") (4=4 "strongly disagree") (2=2 "tend to agree") (3=3 "tend to disagree"), gen(threat6)
{txt}(333 differences between Q1f and threat6)

{com}. * threat7
. recode Q1g (5=.) (1=1 "strongly agree") (4=4 "strongly disagree") (2=2 "tend to agree") (3=3 "tend to disagree"), gen(threat7)
{txt}(419 differences between Q1g and threat7)

{com}. 
. label var threat1 "Violence in Neighbourhood"
{txt}
{com}. label var threat2 "Individual Economic"
{txt}
{com}. label var threat3 "Violence in Society"
{txt}
{com}. label var threat4 "British Culture"
{txt}
{com}. label var threat5 "Collective Economic"
{txt}
{com}. label var threat6 "Britain Better"
{txt}
{com}. label var threat7 "Neighbourhood Nicer"
{txt}
{com}. 
. * education
. gen edu_age=Education_age
{txt}
{com}. recode edu_age (7=.) (1=15) (2=16) (3=17.5) (4=19) (5=20)
{txt}(edu_age: 1576 changes made)

{com}. replace edu_age=Age if edu_age==6
{txt}(112 real changes made)

{com}. recode edu_age (21/100 = 20)
{txt}(edu_age: 50 changes made)

{com}. label var edu_age "terminal age of education"
{txt}
{com}. 
. * age already exists (no missing)
. tab Age

        {txt}Age {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
         18 {c |}{res}         25        1.48        1.48
{txt}         19 {c |}{res}         30        1.78        3.26
{txt}         20 {c |}{res}         30        1.78        5.04
{txt}         21 {c |}{res}         29        1.72        6.75
{txt}         22 {c |}{res}         21        1.24        8.00
{txt}         23 {c |}{res}         36        2.13       10.13
{txt}         24 {c |}{res}         22        1.30       11.43
{txt}         25 {c |}{res}         28        1.66       13.09
{txt}         26 {c |}{res}         25        1.48       14.57
{txt}         27 {c |}{res}         27        1.60       16.17
{txt}         28 {c |}{res}         27        1.60       17.77
{txt}         29 {c |}{res}         26        1.54       19.31
{txt}         30 {c |}{res}         24        1.42       20.73
{txt}         31 {c |}{res}         27        1.60       22.33
{txt}         32 {c |}{res}         20        1.18       23.52
{txt}         33 {c |}{res}         22        1.30       24.82
{txt}         34 {c |}{res}         25        1.48       26.30
{txt}         35 {c |}{res}         22        1.30       27.61
{txt}         36 {c |}{res}         25        1.48       29.09
{txt}         37 {c |}{res}         34        2.01       31.10
{txt}         38 {c |}{res}         26        1.54       32.64
{txt}         39 {c |}{res}         11        0.65       33.29
{txt}         40 {c |}{res}         31        1.84       35.13
{txt}         41 {c |}{res}         16        0.95       36.08
{txt}         42 {c |}{res}         20        1.18       37.26
{txt}         43 {c |}{res}         27        1.60       38.86
{txt}         44 {c |}{res}         27        1.60       40.46
{txt}         45 {c |}{res}         29        1.72       42.18
{txt}         46 {c |}{res}         33        1.95       44.14
{txt}         47 {c |}{res}         33        1.95       46.09
{txt}         48 {c |}{res}         26        1.54       47.63
{txt}         49 {c |}{res}         48        2.84       50.47
{txt}         50 {c |}{res}         19        1.13       51.60
{txt}         51 {c |}{res}         20        1.18       52.78
{txt}         52 {c |}{res}         27        1.60       54.38
{txt}         53 {c |}{res}         31        1.84       56.22
{txt}         54 {c |}{res}         25        1.48       57.70
{txt}         55 {c |}{res}         25        1.48       59.18
{txt}         56 {c |}{res}         33        1.95       61.14
{txt}         57 {c |}{res}         32        1.90       63.03
{txt}         58 {c |}{res}         28        1.66       64.69
{txt}         59 {c |}{res}         24        1.42       66.11
{txt}         60 {c |}{res}         32        1.90       68.01
{txt}         61 {c |}{res}         35        2.07       70.08
{txt}         62 {c |}{res}         38        2.25       72.33
{txt}         63 {c |}{res}         28        1.66       73.99
{txt}         64 {c |}{res}         33        1.95       75.95
{txt}         65 {c |}{res}         33        1.95       77.90
{txt}         66 {c |}{res}         33        1.95       79.86
{txt}         67 {c |}{res}         43        2.55       82.41
{txt}         68 {c |}{res}         48        2.84       85.25
{txt}         69 {c |}{res}         54        3.20       88.45
{txt}         70 {c |}{res}         32        1.90       90.34
{txt}         71 {c |}{res}         20        1.18       91.53
{txt}         72 {c |}{res}         36        2.13       93.66
{txt}         73 {c |}{res}         19        1.13       94.79
{txt}         74 {c |}{res}         12        0.71       95.50
{txt}         75 {c |}{res}         14        0.83       96.33
{txt}         76 {c |}{res}          8        0.47       96.80
{txt}         77 {c |}{res}         11        0.65       97.45
{txt}         78 {c |}{res}          8        0.47       97.93
{txt}         79 {c |}{res}          8        0.47       98.40
{txt}         80 {c |}{res}          6        0.36       98.76
{txt}         81 {c |}{res}          6        0.36       99.11
{txt}         82 {c |}{res}          5        0.30       99.41
{txt}         83 {c |}{res}          2        0.12       99.53
{txt}         84 {c |}{res}          1        0.06       99.59
{txt}         85 {c |}{res}          1        0.06       99.64
{txt}         86 {c |}{res}          2        0.12       99.76
{txt}         88 {c |}{res}          1        0.06       99.82
{txt}         89 {c |}{res}          1        0.06       99.88
{txt}         90 {c |}{res}          1        0.06       99.94
{txt}        101 {c |}{res}          1        0.06      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}      1,688      100.00
{txt}
{com}. 
. * female (no missing)
. recode Gender (1=0 "male") (2=1 "female"), into(female)
{txt}(1688 differences between Gender and female)

{com}. 
. * social grade already exists, but different from w1 (no missing) so recode to match
. tab Socialgrade

     {txt}Social {c |}
      Grade {c |}
     (Chief {c |}
     Income {c |}
Earner) A / {c |}
B / C1 / C2 {c |}
    / D / E {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          a {c |}{res}        205       12.14       12.14
{txt}          b {c |}{res}        324       19.19       31.34
{txt}         C1 {c |}{res}        508       30.09       61.43
{txt}         C2 {c |}{res}        292       17.30       78.73
{txt}          d {c |}{res}        170       10.07       88.80
{txt}          e {c |}{res}        189       11.20      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}      1,688      100.00
{txt}
{com}. recode Socialgrade (1 2=1 "AB") (3=2 "C1") (4=3 "C2") (5 6=4 "DE"), gen(SocialGrade)
{txt}(1483 differences between Socialgrade and SocialGrade)

{com}. 
. * work status already exists (no missing)
. ** Note: to be recoded after imputation
. tab Work_stat

                 {txt}Employment Status Main {c |}      Freq.     Percent        Cum.
{hline 40}{c +}{hline 35}
Working full time (30 or more hours per {c |}{res}        651       38.57       38.57
{txt}  Working part time (8-29 hours a week) {c |}{res}        205       12.14       50.71
{txt}Working part time (Less than 8 hours a  {c |}{res}         38        2.25       52.96
{txt}                      Full time student {c |}{res}        107        6.34       59.30
{txt}                                Retired {c |}{res}        452       26.78       86.08
{txt}                             Unemployed {c |}{res}         56        3.32       89.40
{txt}                            Not working {c |}{res}        129        7.64       97.04
{txt}                                  Other {c |}{res}         50        2.96      100.00
{txt}{hline 40}{c +}{hline 35}
                                  Total {c |}{res}      1,688      100.00
{txt}
{com}. 
. * UKborn
. recode Birthplace (1=1 "inside the UK (ENG, WAL, SCO, NIR)") (2=0 "outside the UK") (3=.), gen(UKborn)
{txt}(124 differences between Birthplace and UKborn)

{com}. label var UKborn "born inside the UK"
{txt}
{com}. 
. * ethnicity already exists
. tab Ethnicity if Ethnicity<2

                 {txt}Ethnicity {c |}      Freq.     Percent        Cum.
{hline 27}{c +}{hline 35}
             White British {c |}{res}      1,514      100.00      100.00
{txt}{hline 27}{c +}{hline 35}
                     Total {c |}{res}      1,514      100.00
{txt}
{com}. ** white British only
. 
. * authoritarianism
. recode Q2a (5=.) (1=4) (4=1) (2=3) (3=2), gen(auth1)
{txt}(1688 differences between Q2a and auth1)

{com}. recode Q2b (5=.) (1=4) (4=1) (2=3) (3=2), gen(auth2)
{txt}(1688 differences between Q2b and auth2)

{com}. recode Q2c (5=.) (1=4) (4=1) (2=3) (3=2), gen(auth3)
{txt}(1688 differences between Q2c and auth3)

{com}. label define authl 1 "strongly disagree" 2 "tend to disagree" 3 "tend to agree" 4 "strongly agree"
{txt}
{com}. label value auth1 authl
{txt}
{com}. label value auth2 authl
{txt}
{com}. label value auth3 authl
{txt}
{com}. 
. * self-esteem
. recode Q3a (1=1 "True") (2=0 "False") (3=.), gen(est1)
{txt}(1272 differences between Q3a and est1)

{com}. recode Q3b (1=1 "True") (2=0 "False") (3=.), gen(est2)
{txt}(1348 differences between Q3b and est2)

{com}. recode Q3c (1=1 "True") (2=0 "False") (3=.), gen(est3)
{txt}(891 differences between Q3c and est3)

{com}. recode Q3d (1=1 "True") (2=0 "False") (3=.), gen(est4)
{txt}(1234 differences between Q3d and est4)

{com}. recode Q3e (1=1 "True") (2=0 "False") (3=.), gen(est5)
{txt}(1085 differences between Q3e and est5)

{com}. 
. * group hostility
. recode Qblack1 (5=.) (1=1) (2=2) (3=3) (4=4), gen(GHbb1)
{txt}(423 differences between Qblack1 and GHbb1)

{com}. recode Qblack2 (5=.) (1=4) (4=1) (2=3) (3=2), gen(GHbb2)
{txt}(1688 differences between Qblack2 and GHbb2)

{com}. recode Qblack3 (5=.) (1=1) (2=2) (3=3) (4=4), gen(GHbb3)
{txt}(362 differences between Qblack3 and GHbb3)

{com}. recode Qblack4 (5=.) (1=4) (4=1) (2=3) (3=2), gen(GHbb4)
{txt}(1688 differences between Qblack4 and GHbb4)

{com}. recode Qblack5 (5=.) (1=4) (4=1) (2=3) (3=2), gen(GHbb5)
{txt}(1688 differences between Qblack5 and GHbb5)

{com}. recode Qblack6 (5=.) (1=4) (4=1) (2=3) (3=2), gen(GHbb6)
{txt}(1688 differences between Qblack6 and GHbb6)

{com}. recode Qblack7 (5=.) (1=4) (4=1) (2=3) (3=2), gen(GHbb7)
{txt}(1688 differences between Qblack7 and GHbb7)

{com}. recode Qblack8 (5=.) (1=4) (4=1) (2=3) (3=2), gen(GHbb8)
{txt}(1688 differences between Qblack8 and GHbb8)

{com}. 
. recode Qmuslim1 (5=.) (1=1) (2=2) (3=3) (4=4), gen(GHmu1)
{txt}(422 differences between Qmuslim1 and GHmu1)

{com}. recode Qmuslim2 (5=.) (1=4) (4=1) (2=3) (3=2), gen(GHmu2)
{txt}(1688 differences between Qmuslim2 and GHmu2)

{com}. recode Qmuslim3 (5=.) (1=1) (2=2) (3=3) (4=4), gen(GHmu3)
{txt}(337 differences between Qmuslim3 and GHmu3)

{com}. recode Qmuslim4 (5=.) (1=4) (4=1) (2=3) (3=2), gen(GHmu4)
{txt}(1688 differences between Qmuslim4 and GHmu4)

{com}. recode Qmuslim5 (5=.) (1=4) (4=1) (2=3) (3=2), gen(GHmu5)
{txt}(1688 differences between Qmuslim5 and GHmu5)

{com}. recode Qmuslim6 (5=.) (1=4) (4=1) (2=3) (3=2), gen(GHmu6)
{txt}(1688 differences between Qmuslim6 and GHmu6)

{com}. recode Qmuslim7 (5=.) (1=4) (4=1) (2=3) (3=2), gen(GHmu7)
{txt}(1688 differences between Qmuslim7 and GHmu7)

{com}. recode Qmuslim8 (5=.) (1=4) (4=1) (2=3) (3=2), gen(GHmu8)
{txt}(1688 differences between Qmuslim8 and GHmu8)

{com}. 
. recode Qeast1 (5=.) (1=1) (2=2) (3=3) (4=4), gen(GHee1)
{txt}(454 differences between Qeast1 and GHee1)

{com}. recode Qeast2 (5=.) (1=4) (4=1) (2=3) (3=2), gen(GHee2)
{txt}(1688 differences between Qeast2 and GHee2)

{com}. recode Qeast3 (5=.) (1=1) (2=2) (3=3) (4=4), gen(GHee3)
{txt}(388 differences between Qeast3 and GHee3)

{com}. recode Qeast4 (5=.) (1=4) (4=1) (2=3) (3=2), gen(GHee4)
{txt}(1688 differences between Qeast4 and GHee4)

{com}. recode Qeast5 (5=.) (1=4) (4=1) (2=3) (3=2), gen(GHee5)
{txt}(1688 differences between Qeast5 and GHee5)

{com}. recode Qeast6 (5=.) (1=4) (4=1) (2=3) (3=2), gen(GHee6)
{txt}(1688 differences between Qeast6 and GHee6)

{com}. recode Qeast7 (5=.) (1=4) (4=1) (2=3) (3=2), gen(GHee7)
{txt}(1688 differences between Qeast7 and GHee7)

{com}. recode Qeast8 (5=.) (1=4) (4=1) (2=3) (3=2), gen(GHee8)
{txt}(1688 differences between Qeast8 and GHee8)

{com}. 
. recode Qwhite1 (5=.) (1=1) (2=2) (3=3) (4=4), gen(GHwb1)
{txt}(339 differences between Qwhite1 and GHwb1)

{com}. recode Qwhite2 (5=.) (1=4) (4=1) (2=3) (3=2), gen(GHwb2)
{txt}(1688 differences between Qwhite2 and GHwb2)

{com}. recode Qwhite3 (5=.) (1=1) (2=2) (3=3) (4=4), gen(GHwb3)
{txt}(268 differences between Qwhite3 and GHwb3)

{com}. recode Qwhite4 (5=.) (1=4) (4=1) (2=3) (3=2), gen(GHwb4)
{txt}(1688 differences between Qwhite4 and GHwb4)

{com}. recode Qwhite5 (5=.) (1=4) (4=1) (2=3) (3=2), gen(GHwb5)
{txt}(1688 differences between Qwhite5 and GHwb5)

{com}. recode Qwhite6 (5=.) (1=4) (4=1) (2=3) (3=2), gen(GHwb6)
{txt}(1688 differences between Qwhite6 and GHwb6)

{com}. recode Qwhite7 (5=.) (1=4) (4=1) (2=3) (3=2), gen(GHwb7)
{txt}(1688 differences between Qwhite7 and GHwb7)

{com}. recode Qwhite8 (5=.) (1=4) (4=1) (2=3) (3=2), gen(GHwb8)
{txt}(1688 differences between Qwhite8 and GHwb8)

{com}. 
. 
. *********************************************************************
. * TABLE A.2B IN THE APPENDIX:
. *       Descriptive Statistics of Independent Variables, 2016 
. *       (before multiple imputation) 
. *********************************************************************
. 
. * keep only White British respondents:
. keep if Ethnicity==1
{txt}(174 observations deleted)

{com}. ** Note: 174 respondents deleted
. 
. * descriptives before imputation, for non-imputed variables only
. ** NOTE: temporarily create i.work_status, then delete and re-do after imputation
. 
. * work status (already 31 missing in original code (coded with missing value code .a)
. recode Work_stat (1=1) (2/3 =2) (4=3) (5=4) (6=5) (7/8 = 6), into(work_status)
{txt}(762 differences between Work_stat and work_status)

{com}. label define work_status 1 "working full time" 2 "working part time" 3 "full time student" 4 "retired" 5 "unemployed" 6 "not working"
{txt}
{com}. label value work_status work_status
{txt}
{com}. label var work_status "working status"
{txt}
{com}. 
. * (decoupled) threats:
. sum threat1 threat2 threat3 threat4 threat5

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 5}threat1 {c |}{res}      1,361    2.215283    .8531611          1          4
{txt}{space 5}threat2 {c |}{res}      1,272    2.697327    .8528523          1          4
{txt}{space 5}threat3 {c |}{res}      1,382     2.84081    .8112971          1          4
{txt}{space 5}threat4 {c |}{res}      1,381    2.754526    .9816373          1          4
{txt}{space 5}threat5 {c |}{res}      1,312    2.727896    .9008255          1          4
{txt}
{com}. * other:
. sum female Age edu_age i.SocialGrade i.work_status UKborn 

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 6}female {c |}{res}      1,514    .5673712     .495604          0          1
{txt}{space 9}Age {c |}{res}      1,514    49.97688    17.40866         18        101
{txt}{space 5}edu_age {c |}{res}      1,504    17.82347    1.848806         15         20
{txt}{space 12} {c |}
{space 1}SocialGrade {c |}
{space 9}C1  {c |}{res}      1,514    .2912814     .454503          0          1
{txt}{hline 13}{c +}{hline 57}
{space 9}C2  {c |}{res}      1,514     .177675    .3823652          0          1
{txt}{space 9}DE  {c |}{res}      1,514    .2107001    .4079406          0          1
{txt}{space 12} {c |}
{space 1}work_status {c |}
working p..  {c |}{res}      1,514    .1453104      .35253          0          1
{txt}full time..  {c |}{res}      1,514    .0581242    .2340554          0          1
{txt}{hline 13}{c +}{hline 57}
{space 4}retired  {c |}{res}      1,514    .2873184    .4526609          0          1
{txt}{space 1}unemployed  {c |}{res}      1,514    .0303831    .1716957          0          1
{txt}not working  {c |}{res}      1,514    .1036988    .3049702          0          1
{txt}{space 12} {c |}
{space 6}UKborn {c |}{res}      1,500        .984    .1255169          0          1
{txt}
{com}. ** to obtain descriptives for first categories of SocialGrade and work_status:
. sum ib(last).SocialGrade ib(last).work_status 

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 1}SocialGrade {c |}
{space 9}AB  {c |}{res}      1,514    .3203435    .4667627          0          1
{txt}{space 9}C1  {c |}{res}      1,514    .2912814     .454503          0          1
{txt}{space 9}C2  {c |}{res}      1,514     .177675    .3823652          0          1
{txt}{space 12} {c |}
{space 1}work_status {c |}
working f..  {c |}{res}      1,514    .3751651    .4843255          0          1
{txt}{hline 13}{c +}{hline 57}
working p..  {c |}{res}      1,514    .1453104      .35253          0          1
{txt}full time..  {c |}{res}      1,514    .0581242    .2340554          0          1
{txt}{space 4}retired  {c |}{res}      1,514    .2873184    .4526609          0          1
{txt}{space 1}unemployed  {c |}{res}      1,514    .0303831    .1716957          0          1
{txt}
{com}. 
. drop work_status
{txt}
{com}. 
. 
. *********************************************************************
. * TABLE A.4B IN THE APPENDIX:  
. *       Associations between Threats under Decoupled Conditions, 2016
. *********************************************************************
. 
. * In order to estimate correlations and their level of significance with survey data:
. * (1) use correlate with aweights for point estimates of the correlation
. * (2) use svy: regress for p-values 
. *       Do svy: regress y x and svy: regress x y and take the biggest p-value, which is the conservative thing to do
. 
. * decoupled
. pwcorr threat1 threat2 threat3 threat4 threat5 [aweight=W8], sig obs

             {txt}{c |}  threat1  threat2  threat3  threat4  threat5
{hline 13}{c +}{hline 45}
     threat1 {c |} {res}  1.0000 
             {txt}{c |}
             {c |}{res}     1361
             {txt}{c |}
     threat2 {c |} {res}  0.2448   1.0000 
             {txt}{c |}{res}   0.0000
             {txt}{c |}{res}     1200     1272
             {txt}{c |}
     threat3 {c |} {res}  0.5456   0.2549   1.0000 
             {txt}{c |}{res}   0.0000   0.0000
             {txt}{c |}{res}     1313     1230     1382
             {txt}{c |}
     threat4 {c |} {res}  0.2909  -0.0684   0.3147   1.0000 
             {txt}{c |}{res}   0.0000   0.0175   0.0000
             {txt}{c |}{res}     1292     1206     1317     1381
             {txt}{c |}
     threat5 {c |} {res}  0.1678   0.6383   0.2030  -0.2501   1.0000 
             {txt}{c |}{res}   0.0000   0.0000   0.0000   0.0000
             {txt}{c |}{res}     1236     1208     1258     1246     1312
             {txt}{c |}

{com}. 
. svyset [pweight=W8]

      {txt}pweight:{col 16}{res}W8
          {txt}VCE:{col 16}{res}linearized
  {txt}Single unit:{col 16}{res}missing
     {txt}Strata 1:{col 16}<one>
         SU 1:{col 16}<observations>
        FPC 1:{col 16}<zero>
{p2colreset}{...}

{com}. svy: reg threat1 threat2 
{txt}(running regress on estimation sample)
{res}
{txt}Survey: Linear regression

{col 1}Number of strata{col 20}= {res}        1{txt}{col 49}Number of obs{col 67}= {res}     1,200
{txt}{col 1}Number of PSUs{col 20}= {res}    1,200{txt}{col 49}Population size{col 67}={res} 1,156.8608
{txt}{col 49}Design df{col 67}= {res}     1,199
{txt}{col 49}F({res}   1{txt},{res}   1199{txt}){col 67}= {res}     56.37
{txt}{col 49}Prob > F{col 67}= {res}    0.0000
{txt}{col 49}R-squared{col 67}= {res}    0.0599

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}  Linearized
{col 1}     threat1{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}threat2 {c |}{col 14}{res}{space 2} .2421034{col 26}{space 2}  .032247{col 37}{space 1}    7.51{col 46}{space 3}0.000{col 54}{space 4} .1788366{col 67}{space 3} .3053703
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 1.579415{col 26}{space 2} .0886662{col 37}{space 1}   17.81{col 46}{space 3}0.000{col 54}{space 4} 1.405457{col 67}{space 3} 1.753374
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. svy: reg threat2 threat1 
{txt}(running regress on estimation sample)
{res}
{txt}Survey: Linear regression

{col 1}Number of strata{col 20}= {res}        1{txt}{col 49}Number of obs{col 67}= {res}     1,200
{txt}{col 1}Number of PSUs{col 20}= {res}    1,200{txt}{col 49}Population size{col 67}={res} 1,156.8608
{txt}{col 49}Design df{col 67}= {res}     1,199
{txt}{col 49}F({res}   1{txt},{res}   1199{txt}){col 67}= {res}     57.24
{txt}{col 49}Prob > F{col 67}= {res}    0.0000
{txt}{col 49}R-squared{col 67}= {res}    0.0599

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}  Linearized
{col 1}     threat2{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}threat1 {c |}{col 14}{res}{space 2} .2474647{col 26}{space 2} .0327093{col 37}{space 1}    7.57{col 46}{space 3}0.000{col 54}{space 4} .1832908{col 67}{space 3} .3116385
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 2.120591{col 26}{space 2} .0778146{col 37}{space 1}   27.25{col 46}{space 3}0.000{col 54}{space 4} 1.967923{col 67}{space 3} 2.273259
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. svy: reg threat1 threat3 
{txt}(running regress on estimation sample)
{res}
{txt}Survey: Linear regression

{col 1}Number of strata{col 20}= {res}        1{txt}{col 49}Number of obs{col 67}= {res}     1,313
{txt}{col 1}Number of PSUs{col 20}= {res}    1,313{txt}{col 49}Population size{col 67}={res} 1,273.5304
{txt}{col 49}Design df{col 67}= {res}     1,312
{txt}{col 49}F({res}   1{txt},{res}   1312{txt}){col 67}= {res}    452.37
{txt}{col 49}Prob > F{col 67}= {res}    0.0000
{txt}{col 49}R-squared{col 67}= {res}    0.2976

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}  Linearized
{col 1}     threat1{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}threat3 {c |}{col 14}{res}{space 2} .5693558{col 26}{space 2} .0267694{col 37}{space 1}   21.27{col 46}{space 3}0.000{col 54}{space 4} .5168403{col 67}{space 3} .6218713
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .6435282{col 26}{space 2} .0726153{col 37}{space 1}    8.86{col 46}{space 3}0.000{col 54}{space 4} .5010733{col 67}{space 3}  .785983
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. svy: reg threat3 threat1 
{txt}(running regress on estimation sample)
{res}
{txt}Survey: Linear regression

{col 1}Number of strata{col 20}= {res}        1{txt}{col 49}Number of obs{col 67}= {res}     1,313
{txt}{col 1}Number of PSUs{col 20}= {res}    1,313{txt}{col 49}Population size{col 67}={res} 1,273.5304
{txt}{col 49}Design df{col 67}= {res}     1,312
{txt}{col 49}F({res}   1{txt},{res}   1312{txt}){col 67}= {res}    477.54
{txt}{col 49}Prob > F{col 67}= {res}    0.0000
{txt}{col 49}R-squared{col 67}= {res}    0.2976

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}  Linearized
{col 1}     threat3{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}threat1 {c |}{col 14}{res}{space 2} .5227433{col 26}{space 2} .0239213{col 37}{space 1}   21.85{col 46}{space 3}0.000{col 54}{space 4} .4758151{col 67}{space 3} .5696715
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 1.644329{col 26}{space 2} .0626446{col 37}{space 1}   26.25{col 46}{space 3}0.000{col 54}{space 4} 1.521435{col 67}{space 3} 1.767224
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. svy: reg threat1 threat4 
{txt}(running regress on estimation sample)
{res}
{txt}Survey: Linear regression

{col 1}Number of strata{col 20}= {res}        1{txt}{col 49}Number of obs{col 67}= {res}     1,292
{txt}{col 1}Number of PSUs{col 20}= {res}    1,292{txt}{col 49}Population size{col 67}={res} 1,256.0834
{txt}{col 49}Design df{col 67}= {res}     1,291
{txt}{col 49}F({res}   1{txt},{res}   1291{txt}){col 67}= {res}     88.02
{txt}{col 49}Prob > F{col 67}= {res}    0.0000
{txt}{col 49}R-squared{col 67}= {res}    0.0846

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}  Linearized
{col 1}     threat1{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}threat4 {c |}{col 14}{res}{space 2}  .256127{col 26}{space 2} .0273003{col 37}{space 1}    9.38{col 46}{space 3}0.000{col 54}{space 4} .2025692{col 67}{space 3} .3096849
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 1.525995{col 26}{space 2} .0772876{col 37}{space 1}   19.74{col 46}{space 3}0.000{col 54}{space 4} 1.374372{col 67}{space 3} 1.677618
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. svy: reg threat4 threat1 
{txt}(running regress on estimation sample)
{res}
{txt}Survey: Linear regression

{col 1}Number of strata{col 20}= {res}        1{txt}{col 49}Number of obs{col 67}= {res}     1,292
{txt}{col 1}Number of PSUs{col 20}= {res}    1,292{txt}{col 49}Population size{col 67}={res} 1,256.0834
{txt}{col 49}Design df{col 67}= {res}     1,291
{txt}{col 49}F({res}   1{txt},{res}   1291{txt}){col 67}= {res}     93.44
{txt}{col 49}Prob > F{col 67}= {res}    0.0000
{txt}{col 49}R-squared{col 67}= {res}    0.0846

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}  Linearized
{col 1}     threat4{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}threat1 {c |}{col 14}{res}{space 2} .3303102{col 26}{space 2} .0341707{col 37}{space 1}    9.67{col 46}{space 3}0.000{col 54}{space 4}  .263274{col 67}{space 3} .3973465
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 2.046966{col 26}{space 2} .0820355{col 37}{space 1}   24.95{col 46}{space 3}0.000{col 54}{space 4} 1.886029{col 67}{space 3} 2.207904
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. svy: reg threat1 threat5 
{txt}(running regress on estimation sample)
{res}
{txt}Survey: Linear regression

{col 1}Number of strata{col 20}= {res}        1{txt}{col 49}Number of obs{col 67}= {res}     1,236
{txt}{col 1}Number of PSUs{col 20}= {res}    1,236{txt}{col 49}Population size{col 67}={res} 1,192.1922
{txt}{col 49}Design df{col 67}= {res}     1,235
{txt}{col 49}F({res}   1{txt},{res}   1235{txt}){col 67}= {res}     25.27
{txt}{col 49}Prob > F{col 67}= {res}    0.0000
{txt}{col 49}R-squared{col 67}= {res}    0.0282

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}  Linearized
{col 1}     threat1{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}threat5 {c |}{col 14}{res}{space 2} .1601181{col 26}{space 2} .0318506{col 37}{space 1}    5.03{col 46}{space 3}0.000{col 54}{space 4} .0976307{col 67}{space 3} .2226054
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 1.803477{col 26}{space 2} .0893199{col 37}{space 1}   20.19{col 46}{space 3}0.000{col 54}{space 4} 1.628242{col 67}{space 3} 1.978713
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. svy: reg threat5 threat1 
{txt}(running regress on estimation sample)
{res}
{txt}Survey: Linear regression

{col 1}Number of strata{col 20}= {res}        1{txt}{col 49}Number of obs{col 67}= {res}     1,236
{txt}{col 1}Number of PSUs{col 20}= {res}    1,236{txt}{col 49}Population size{col 67}={res} 1,192.1922
{txt}{col 49}Design df{col 67}= {res}     1,235
{txt}{col 49}F({res}   1{txt},{res}   1235{txt}){col 67}= {res}     25.25
{txt}{col 49}Prob > F{col 67}= {res}    0.0000
{txt}{col 49}R-squared{col 67}= {res}    0.0282

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}  Linearized
{col 1}     threat5{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}threat1 {c |}{col 14}{res}{space 2} .1759163{col 26}{space 2} .0350069{col 37}{space 1}    5.03{col 46}{space 3}0.000{col 54}{space 4} .1072368{col 67}{space 3} .2445958
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 2.292286{col 26}{space 2} .0819564{col 37}{space 1}   27.97{col 46}{space 3}0.000{col 54}{space 4} 2.131497{col 67}{space 3} 2.453075
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. svy: reg threat2 threat3 
{txt}(running regress on estimation sample)
{res}
{txt}Survey: Linear regression

{col 1}Number of strata{col 20}= {res}        1{txt}{col 49}Number of obs{col 67}= {res}     1,230
{txt}{col 1}Number of PSUs{col 20}= {res}    1,230{txt}{col 49}Population size{col 67}={res}  1,186.354
{txt}{col 49}Design df{col 67}= {res}     1,229
{txt}{col 49}F({res}   1{txt},{res}   1229{txt}){col 67}= {res}     62.58
{txt}{col 49}Prob > F{col 67}= {res}    0.0000
{txt}{col 49}R-squared{col 67}= {res}    0.0650

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}  Linearized
{col 1}     threat2{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}threat3 {c |}{col 14}{res}{space 2} .2636382{col 26}{space 2} .0333269{col 37}{space 1}    7.91{col 46}{space 3}0.000{col 54}{space 4} .1982543{col 67}{space 3} .3290221
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 1.935489{col 26}{space 2} .0974658{col 37}{space 1}   19.86{col 46}{space 3}0.000{col 54}{space 4} 1.744271{col 67}{space 3} 2.126707
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. svy: reg threat3 threat2 
{txt}(running regress on estimation sample)
{res}
{txt}Survey: Linear regression

{col 1}Number of strata{col 20}= {res}        1{txt}{col 49}Number of obs{col 67}= {res}     1,230
{txt}{col 1}Number of PSUs{col 20}= {res}    1,230{txt}{col 49}Population size{col 67}={res}  1,186.354
{txt}{col 49}Design df{col 67}= {res}     1,229
{txt}{col 49}F({res}   1{txt},{res}   1229{txt}){col 67}= {res}     61.66
{txt}{col 49}Prob > F{col 67}= {res}    0.0000
{txt}{col 49}R-squared{col 67}= {res}    0.0650

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}  Linearized
{col 1}     threat3{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}threat2 {c |}{col 14}{res}{space 2} .2465295{col 26}{space 2} .0313956{col 37}{space 1}    7.85{col 46}{space 3}0.000{col 54}{space 4} .1849346{col 67}{space 3} .3081245
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 2.171557{col 26}{space 2} .0894417{col 37}{space 1}   24.28{col 46}{space 3}0.000{col 54}{space 4} 1.996081{col 67}{space 3} 2.347032
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. svy: reg threat2 threat4 
{txt}(running regress on estimation sample)
{res}
{txt}Survey: Linear regression

{col 1}Number of strata{col 20}= {res}        1{txt}{col 49}Number of obs{col 67}= {res}     1,206
{txt}{col 1}Number of PSUs{col 20}= {res}    1,206{txt}{col 49}Population size{col 67}={res}  1,161.495
{txt}{col 49}Design df{col 67}= {res}     1,205
{txt}{col 49}F({res}   1{txt},{res}   1205{txt}){col 67}= {res}      4.32
{txt}{col 49}Prob > F{col 67}= {res}    0.0380
{txt}{col 49}R-squared{col 67}= {res}    0.0047

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}  Linearized
{col 1}     threat2{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}threat4 {c |}{col 14}{res}{space 2} -.059823{col 26}{space 2} .0287945{col 37}{space 1}   -2.08{col 46}{space 3}0.038{col 54}{space 4}-.1163158{col 67}{space 3}-.0033301
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 2.840642{col 26}{space 2} .0854628{col 37}{space 1}   33.24{col 46}{space 3}0.000{col 54}{space 4} 2.672969{col 67}{space 3} 3.008314
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. svy: reg threat4 threat2 
{txt}(running regress on estimation sample)
{res}
{txt}Survey: Linear regression

{col 1}Number of strata{col 20}= {res}        1{txt}{col 49}Number of obs{col 67}= {res}     1,206
{txt}{col 1}Number of PSUs{col 20}= {res}    1,206{txt}{col 49}Population size{col 67}={res}  1,161.495
{txt}{col 49}Design df{col 67}= {res}     1,205
{txt}{col 49}F({res}   1{txt},{res}   1205{txt}){col 67}= {res}      4.25
{txt}{col 49}Prob > F{col 67}= {res}    0.0396
{txt}{col 49}R-squared{col 67}= {res}    0.0047

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}  Linearized
{col 1}     threat4{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}threat2 {c |}{col 14}{res}{space 2}-.0782819{col 26}{space 2} .0379921{col 37}{space 1}   -2.06{col 46}{space 3}0.040{col 54}{space 4}-.1528199{col 67}{space 3} -.003744
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 2.971478{col 26}{space 2} .1035894{col 37}{space 1}   28.69{col 46}{space 3}0.000{col 54}{space 4} 2.768242{col 67}{space 3} 3.174714
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. svy: reg threat2 threat5 
{txt}(running regress on estimation sample)
{res}
{txt}Survey: Linear regression

{col 1}Number of strata{col 20}= {res}        1{txt}{col 49}Number of obs{col 67}= {res}     1,208
{txt}{col 1}Number of PSUs{col 20}= {res}    1,208{txt}{col 49}Population size{col 67}={res}  1,160.315
{txt}{col 49}Design df{col 67}= {res}     1,207
{txt}{col 49}F({res}   1{txt},{res}   1207{txt}){col 67}= {res}    599.88
{txt}{col 49}Prob > F{col 67}= {res}    0.0000
{txt}{col 49}R-squared{col 67}= {res}    0.4074

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}  Linearized
{col 1}     threat2{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}threat5 {c |}{col 14}{res}{space 2} .6032772{col 26}{space 2} .0246311{col 37}{space 1}   24.49{col 46}{space 3}0.000{col 54}{space 4} .5549527{col 67}{space 3} .6516018
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 1.053901{col 26}{space 2} .0720113{col 37}{space 1}   14.64{col 46}{space 3}0.000{col 54}{space 4} .9126198{col 67}{space 3} 1.195182
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. svy: reg threat5 threat2 
{txt}(running regress on estimation sample)
{res}
{txt}Survey: Linear regression

{col 1}Number of strata{col 20}= {res}        1{txt}{col 49}Number of obs{col 67}= {res}     1,208
{txt}{col 1}Number of PSUs{col 20}= {res}    1,208{txt}{col 49}Population size{col 67}={res}  1,160.315
{txt}{col 49}Design df{col 67}= {res}     1,207
{txt}{col 49}F({res}   1{txt},{res}   1207{txt}){col 67}= {res}    602.33
{txt}{col 49}Prob > F{col 67}= {res}    0.0000
{txt}{col 49}R-squared{col 67}= {res}    0.4074

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}  Linearized
{col 1}     threat5{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}threat2 {c |}{col 14}{res}{space 2} .6752779{col 26}{space 2} .0275148{col 37}{space 1}   24.54{col 46}{space 3}0.000{col 54}{space 4} .6212957{col 67}{space 3} .7292601
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .8988449{col 26}{space 2} .0780442{col 37}{space 1}   11.52{col 46}{space 3}0.000{col 54}{space 4} .7457275{col 67}{space 3} 1.051962
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. svy: reg threat3 threat4 
{txt}(running regress on estimation sample)
{res}
{txt}Survey: Linear regression

{col 1}Number of strata{col 20}= {res}        1{txt}{col 49}Number of obs{col 67}= {res}     1,317
{txt}{col 1}Number of PSUs{col 20}= {res}    1,317{txt}{col 49}Population size{col 67}={res} 1,276.5783
{txt}{col 49}Design df{col 67}= {res}     1,316
{txt}{col 49}F({res}   1{txt},{res}   1316{txt}){col 67}= {res}    103.13
{txt}{col 49}Prob > F{col 67}= {res}    0.0000
{txt}{col 49}R-squared{col 67}= {res}    0.0991

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}  Linearized
{col 1}     threat3{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}threat4 {c |}{col 14}{res}{space 2} .2671179{col 26}{space 2} .0263028{col 37}{space 1}   10.16{col 46}{space 3}0.000{col 54}{space 4} .2155178{col 67}{space 3} .3187179
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 2.082854{col 26}{space 2} .0786514{col 37}{space 1}   26.48{col 46}{space 3}0.000{col 54}{space 4} 1.928558{col 67}{space 3} 2.237149
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. svy: reg threat4 threat3 
{txt}(running regress on estimation sample)
{res}
{txt}Survey: Linear regression

{col 1}Number of strata{col 20}= {res}        1{txt}{col 49}Number of obs{col 67}= {res}     1,317
{txt}{col 1}Number of PSUs{col 20}= {res}    1,317{txt}{col 49}Population size{col 67}={res} 1,276.5783
{txt}{col 49}Design df{col 67}= {res}     1,316
{txt}{col 49}F({res}   1{txt},{res}   1316{txt}){col 67}= {res}    108.01
{txt}{col 49}Prob > F{col 67}= {res}    0.0000
{txt}{col 49}R-squared{col 67}= {res}    0.0991

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}  Linearized
{col 1}     threat4{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}threat3 {c |}{col 14}{res}{space 2} .3708623{col 26}{space 2} .0356843{col 37}{space 1}   10.39{col 46}{space 3}0.000{col 54}{space 4}  .300858{col 67}{space 3} .4408666
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 1.753233{col 26}{space 2} .1041507{col 37}{space 1}   16.83{col 46}{space 3}0.000{col 54}{space 4} 1.548914{col 67}{space 3} 1.957553
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. svy: reg threat3 threat5 
{txt}(running regress on estimation sample)
{res}
{txt}Survey: Linear regression

{col 1}Number of strata{col 20}= {res}        1{txt}{col 49}Number of obs{col 67}= {res}     1,258
{txt}{col 1}Number of PSUs{col 20}= {res}    1,258{txt}{col 49}Population size{col 67}={res} 1,217.1427
{txt}{col 49}Design df{col 67}= {res}     1,257
{txt}{col 49}F({res}   1{txt},{res}   1257{txt}){col 67}= {res}     40.64
{txt}{col 49}Prob > F{col 67}= {res}    0.0000
{txt}{col 49}R-squared{col 67}= {res}    0.0412

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}  Linearized
{col 1}     threat3{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}threat5 {c |}{col 14}{res}{space 2} .1864914{col 26}{space 2} .0292522{col 37}{space 1}    6.38{col 46}{space 3}0.000{col 54}{space 4} .1291028{col 67}{space 3} .2438799
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 2.327002{col 26}{space 2} .0845847{col 37}{space 1}   27.51{col 46}{space 3}0.000{col 54}{space 4}  2.16106{col 67}{space 3} 2.492945
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. svy: reg threat5 threat3 
{txt}(running regress on estimation sample)
{res}
{txt}Survey: Linear regression

{col 1}Number of strata{col 20}= {res}        1{txt}{col 49}Number of obs{col 67}= {res}     1,258
{txt}{col 1}Number of PSUs{col 20}= {res}    1,258{txt}{col 49}Population size{col 67}={res} 1,217.1427
{txt}{col 49}Design df{col 67}= {res}     1,257
{txt}{col 49}F({res}   1{txt},{res}   1257{txt}){col 67}= {res}     39.69
{txt}{col 49}Prob > F{col 67}= {res}    0.0000
{txt}{col 49}R-squared{col 67}= {res}    0.0412

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}  Linearized
{col 1}     threat5{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}threat3 {c |}{col 14}{res}{space 2} .2209675{col 26}{space 2} .0350737{col 37}{space 1}    6.30{col 46}{space 3}0.000{col 54}{space 4}  .152158{col 67}{space 3} .2897769
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 2.073441{col 26}{space 2} .1023121{col 37}{space 1}   20.27{col 46}{space 3}0.000{col 54}{space 4} 1.872719{col 67}{space 3} 2.274162
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. svy: reg threat4 threat5 
{txt}(running regress on estimation sample)
{res}
{txt}Survey: Linear regression

{col 1}Number of strata{col 20}= {res}        1{txt}{col 49}Number of obs{col 67}= {res}     1,246
{txt}{col 1}Number of PSUs{col 20}= {res}    1,246{txt}{col 49}Population size{col 67}={res} 1,202.4204
{txt}{col 49}Design df{col 67}= {res}     1,245
{txt}{col 49}F({res}   1{txt},{res}   1245{txt}){col 67}= {res}     63.03
{txt}{col 49}Prob > F{col 67}= {res}    0.0000
{txt}{col 49}R-squared{col 67}= {res}    0.0625

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}  Linearized
{col 1}     threat4{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}threat5 {c |}{col 14}{res}{space 2}-.2725119{col 26}{space 2} .0343255{col 37}{space 1}   -7.94{col 46}{space 3}0.000{col 54}{space 4}-.3398542{col 67}{space 3}-.2051696
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 3.510039{col 26}{space 2} .0941521{col 37}{space 1}   37.28{col 46}{space 3}0.000{col 54}{space 4} 3.325324{col 67}{space 3} 3.694753
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. svy: reg threat5 threat4 
{txt}(running regress on estimation sample)
{res}
{txt}Survey: Linear regression

{col 1}Number of strata{col 20}= {res}        1{txt}{col 49}Number of obs{col 67}= {res}     1,246
{txt}{col 1}Number of PSUs{col 20}= {res}    1,246{txt}{col 49}Population size{col 67}={res} 1,202.4204
{txt}{col 49}Design df{col 67}= {res}     1,245
{txt}{col 49}F({res}   1{txt},{res}   1245{txt}){col 67}= {res}     66.28
{txt}{col 49}Prob > F{col 67}= {res}    0.0000
{txt}{col 49}R-squared{col 67}= {res}    0.0625

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}  Linearized
{col 1}     threat5{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}threat4 {c |}{col 14}{res}{space 2}-.2294676{col 26}{space 2} .0281859{col 37}{space 1}   -8.14{col 46}{space 3}0.000{col 54}{space 4}-.2847647{col 67}{space 3}-.1741705
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 3.331588{col 26}{space 2} .0811035{col 37}{space 1}   41.08{col 46}{space 3}0.000{col 54}{space 4} 3.172473{col 67}{space 3} 3.490702
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. svyset, clear
{txt}
{com}. 
. 
. *********************************************************************
. * MULTIPLE IMPUTATION
. *********************************************************************
. 
. * impute (use recoded var in which missing (often code 5) is set to missing "." 
. * only exception is Work_stat and Socialgrade as there is more info in original variables
. 
. set seed 974302623
{txt}
{com}. mi set mlong
{txt}
{com}. mi register imputed auth1 auth2 auth3 est1 est2 est3 est4 est5 GHbb1 GHbb2 GHbb3 GHbb4 GHbb5 GHbb6 GHbb7 GHbb8 GHmu1 GHmu2 GHmu3 GHmu4 GHmu5 GHmu6 GHmu7 GHmu8 GHee1 GHee2 GHee3 GHee4 GHee5 GHee6 GHee7 GHee8 GHwb1 GHwb2 GHwb3 GHwb4 GHwb5 GHwb6 GHwb7 GHwb8 
{res}{txt}{p}
(1025 {it:m}=0 obs. now marked as incomplete)
{p_end}

{com}. mi impute mvn auth1 auth2 auth3 est1 est2 est3 est4 est5 GHbb1 GHbb2 GHbb3 GHbb4 GHbb5 GHbb6 GHbb7 GHbb8 GHmu1 GHmu2 GHmu3 GHmu4 GHmu5 GHmu6 GHmu7 GHmu8 GHee1 GHee2 GHee3 GHee4 GHee5 GHee6 GHee7 GHee8 GHwb1 GHwb2 GHwb3 GHwb4 GHwb5 GHwb6 GHwb7 GHwb8 = female Age edu_age i.Socialgrade i.Work_stat UKborn i.threat1 i.threat2 i.threat3 i.threat4 i.threat5 i.threat6 i.threat7, add(10) force initmcmc(em, iterate(400))
{res}
{txt}Performing EM optimization:
{txt}{p 0 6}note: 2 {txt}observations {txt}omitted from EM estimation because of all {txt}imputation variables missing{p_end}
{txt}  observed log likelihood = {res} 4052.3735{txt} at iteration 21
{res}
{txt}Performing MCMC data augmentation ... 
{res}{txt}
Multivariate imputation{txt}{col 45}{ralign 12:Imputations }= {res}      10
{txt}Multivariate normal regression{txt}{col 45}{ralign 12:added }= {res}      10
{txt}Imputed: {it:m}=1 through {it:m}=10{txt}{col 45}{ralign 12:updated }= {res}       0

{txt}Prior: uniform{txt}{col 45}{ralign 12:Iterations }= {res}    1000
{txt}{col 45}{ralign 12:burn-in }= {res}     100
{txt}{col 45}{ralign 12:between }= {res}     100

{txt}{hline 19}{c TT}{hline 35}{hline 11}
{txt}{col 20}{c |}{center 46:  Observations per {it:m}}
{txt}{col 20}{c LT}{hline 35}{c TT}{hline 10}
{txt}{col 11}Variable {c |}{ralign 12:Complete }{ralign 13:Incomplete }{ralign 10:Imputed }{c |}{ralign 10:Total}
{hline 19}{c +}{hline 35}{c +}{hline 10}
{txt}{ralign 19:auth1 }{c |}{res}       1355          159        41 {txt}{c |}{res}      1514
{txt}{ralign 19:auth2 }{c |}{res}       1349          165        34 {txt}{c |}{res}      1514
{txt}{ralign 19:auth3 }{c |}{res}       1311          203        45 {txt}{c |}{res}      1514
{txt}{ralign 19:est1 }{c |}{res}       1334          180        66 {txt}{c |}{res}      1514
{txt}{ralign 19:est2 }{c |}{res}       1259          255        92 {txt}{c |}{res}      1514
{txt}{ralign 19:est3 }{c |}{res}       1389          125        35 {txt}{c |}{res}      1514
{txt}{ralign 19:est4 }{c |}{res}       1202          312       111 {txt}{c |}{res}      1514
{txt}{ralign 19:est5 }{c |}{res}       1355          159        51 {txt}{c |}{res}      1514
{txt}{ralign 19:GHbb1 }{c |}{res}       1141          373       117 {txt}{c |}{res}      1514
{txt}{ralign 19:GHbb2 }{c |}{res}       1174          340       101 {txt}{c |}{res}      1514
{txt}{ralign 19:GHbb3 }{c |}{res}       1190          324       102 {txt}{c |}{res}      1514
{txt}{ralign 19:GHbb4 }{c |}{res}       1198          316        97 {txt}{c |}{res}      1514
{txt}{ralign 19:GHbb5 }{c |}{res}       1192          322        96 {txt}{c |}{res}      1514
{txt}{ralign 19:GHbb6 }{c |}{res}       1187          327        90 {txt}{c |}{res}      1514
{txt}{ralign 19:GHbb7 }{c |}{res}       1208          306        90 {txt}{c |}{res}      1514
{txt}{ralign 19:GHbb8 }{c |}{res}       1250          264        83 {txt}{c |}{res}      1514
{txt}{ralign 19:GHmu1 }{c |}{res}       1138          376       122 {txt}{c |}{res}      1514
{txt}{ralign 19:GHmu2 }{c |}{res}       1213          301        93 {txt}{c |}{res}      1514
{txt}{ralign 19:GHmu3 }{c |}{res}       1215          299        88 {txt}{c |}{res}      1514
{txt}{ralign 19:GHmu4 }{c |}{res}       1212          302        88 {txt}{c |}{res}      1514
{txt}{ralign 19:GHmu5 }{c |}{res}       1180          334       109 {txt}{c |}{res}      1514
{txt}{ralign 19:GHmu6 }{c |}{res}       1216          298        88 {txt}{c |}{res}      1514
{txt}{ralign 19:GHmu7 }{c |}{res}       1199          315        98 {txt}{c |}{res}      1514
{txt}{ralign 19:GHmu8 }{c |}{res}       1226          288        98 {txt}{c |}{res}      1514
{txt}{ralign 19:GHee1 }{c |}{res}       1114          400       143 {txt}{c |}{res}      1514
{txt}{ralign 19:GHee2 }{c |}{res}       1176          338       107 {txt}{c |}{res}      1514
{txt}{ralign 19:GHee3 }{c |}{res}       1174          340       110 {txt}{c |}{res}      1514
{txt}{ralign 19:GHee4 }{c |}{res}       1181          333       104 {txt}{c |}{res}      1514
{txt}{ralign 19:GHee5 }{c |}{res}       1225          289        94 {txt}{c |}{res}      1514
{txt}{ralign 19:GHee6 }{c |}{res}       1160          354       104 {txt}{c |}{res}      1514
{txt}{ralign 19:GHee7 }{c |}{res}       1171          343       112 {txt}{c |}{res}      1514
{txt}{ralign 19:GHee8 }{c |}{res}       1220          294        96 {txt}{c |}{res}      1514
{txt}{ralign 19:GHwb1 }{c |}{res}       1224          290        83 {txt}{c |}{res}      1514
{txt}{ralign 19:GHwb2 }{c |}{res}       1297          217        50 {txt}{c |}{res}      1514
{txt}{ralign 19:GHwb3 }{c |}{res}       1284          230        61 {txt}{c |}{res}      1514
{txt}{ralign 19:GHwb4 }{c |}{res}       1246          268        70 {txt}{c |}{res}      1514
{txt}{ralign 19:GHwb5 }{c |}{res}       1280          234        59 {txt}{c |}{res}      1514
{txt}{ralign 19:GHwb6 }{c |}{res}       1259          255        67 {txt}{c |}{res}      1514
{txt}{ralign 19:GHwb7 }{c |}{res}       1292          222        54 {txt}{c |}{res}      1514
{txt}{ralign 19:GHwb8 }{c |}{res}       1287          227        62 {txt}{c |}{res}      1514
{txt}{hline 19}{c BT}{hline 35}{c BT}{hline 10}
{p 0 1 1 66}(complete + incomplete = total; imputed is the minimum across {it:m}
 of the number of filled-in observations.){p_end}

{p 0 6 6 71}Note: Right-hand-side variables (or weights) have missing values; model parameters estimated using listwise deletion.{p_end}

{com}. display c(seed)
{res}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
{txt}
{com}. /* state of random-number generator is (Eline: is this necessary to record?): 
> XAAcd5e29d3a216790bc618d7bf600f45f40f42f8f2804760d303eb25acd20a86b64f9a99dbc8bc33ef7206dd0828d4b623f92fdec
> > 5d019b4eaf8b5837005ee0f86d882a799a10f20fb4febfa0a1254519e3d5b09cb3a805873931cf71c16eeb62601a023903b9d463
> > 1b33cb864f6f44dcf31b7c40a96af353298e0be6d11f8a24eb0ae0d1b81540abd9d7c0cb0cf248df3ea3fabe09758b0deadcb57e
> > 3f4deeaabea7fcfde37b8646e59dcce8db6effe4d22f81d3fdd8ec29940e30ced11c2e60cee282c015ed32d84e65f5bc902e2718
> > bcf53f00677c244a3cba2a9ceee207548a66052ad10cba625ed11697304af2ea850e067c54f6ea6bacef2508860288ea83ef3147
> > 1c354c9a5d1cbc6f1dc81f2fd53333b0b89fd5d4f7bbff4586eaabc703ece73dfdd84460e959cbfd7b21f304c93f800cba0862c0
> > e8751b084b5961f4b916b9df32f1eb7271b8096cce014b608473e3a4e680d29989c9f60be995851738a7756bcc193e8d2d29e3c5
> > f65340bc8886cdfa57c77ef7d7d1bd730d782885ab236c36cbb0d4208686fc8f3ad2063bd869a2e188939a0986d4a8bc6391f128
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> > c76c9b325c2e46c991b48dd9ecc810fceab808031e7109bf9aade0ec2de8e832951f9038f43221718463c2f3824904e67a85d5ce
> > efafaa8c99d85a50de1f2d3a94f3a7fc9f67ba4369f482e0a3b121403a80755ad776b176f10002f5f6b44e6e2d0dcd3308b20c69
> > 6103938c4a8f0c44b49e09e5eefe1032f7d3006aa612c040c7c45b60c139901b575e79279ea8a52a3eaef3a516402da67bbea653
> > 30001000000f23515
> */
. 
. save "W4 imputed.dta"
{txt}file W4 imputed.dta saved

{com}. 
. 
. *********************************************************************
. * FURTHER RECODES AND DESCRIPTIVES
. *********************************************************************
. 
. * work status 
. recode Work_stat (1=1) (2/3 =2) (4=3) (5=4) (6=5) (7/8 = 6), into(work_status)
{txt}(6122 differences between Work_stat and work_status)

{com}. label define Work_status 1 "working full time" 2 "working part time" 3 "full time student" 4 "retired" 5 "unemployed" 6 "not working"
{txt}
{com}. label value work_status Work_status
{txt}
{com}. label var work_status "working status"
{txt}
{com}. 
. * authoritarian values, self-esteem and social distance
. gen authvalues = (auth1+ auth2+ auth3)/3 
{txt}(2,660 missing values generated)

{com}. gen selfest = (est1+ est2 +est3 +est4+ est5)/5  
{txt}(4,234 missing values generated)

{com}. gen GHblack = (GHbb1 +GHbb2 +GHbb3 +GHbb4 +GHbb5 +GHbb6 +GHbb7 +GHbb8)/8
{txt}(4,199 missing values generated)

{com}. gen GHMus = (GHmu1 +GHmu2+ GHmu3 +GHmu4 +GHmu5 +GHmu6 +GHmu7 +GHmu8)/8
{txt}(4,401 missing values generated)

{com}. gen GHEEur = (GHee1 +GHee2 +GHee3+ GHee4 +GHee5 +GHee6+ GHee7+ GHee8)/8
{txt}(4,454 missing values generated)

{com}. gen GHwhite = (GHwb1 +GHwb2+ GHwb3 +GHwb4+ GHwb5 +GHwb6 +GHwb7+ GHwb8)/8
{txt}(3,843 missing values generated)

{com}. 
. * weighting
. mi svyset [pweight=W8]
{res}
      {txt}pweight:{col 16}{res}W8
          {txt}VCE:{col 16}{res}linearized
  {txt}Single unit:{col 16}{res}missing
     {txt}Strata 1:{col 16}<one>
         SU 1:{col 16}<observations>
        FPC 1:{col 16}<zero>
{p2colreset}{...}
{res}{txt}
{com}. 
. * create variable indicating survey wave
. gen wave=1
{txt}
{com}. label define wave 0 "survey wave 1 (2011)" 1 "survey wave 4 (2016)"
{txt}
{com}. label value wave wave
{txt}
{com}. label var wave "survey wave"
{txt}
{com}. 
. save "W4 imputed.dta", replace
{txt}file W4 imputed.dta saved

{com}. 
. 
. *********************************************************************
. * TABLE A.3B IN THE APPENDIX:
. *       Estimated Mean and Standard Error of Imputed Variables, 2016
. *********************************************************************
. 
. * descriptives: estimated mean and s.e.
. mi estimate: svy: mean authvalues
{res}
{txt}Multiple-imputation estimates{col 35}Imputations{col 51}= {res}        10
{txt}Survey: Mean estimation{col 35}Number of obs{col 51}= {res}     1,280

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 35}Population size{col 51}={res} 1,226.5711
{txt}{col 1}Number of PSUs{col 19}= {res}    1,280
{txt}{col 35}Average RVI{col 51}= {res}    0.0639
{txt}{col 35}Largest FMI{col 51}= {res}    0.0609
{txt}{col 35}Complete DF{col 51}= {res}      1279
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 35}DF:     min{col 51}= {res}    810.57
{txt}{col 35}        avg{col 51}= {res}    810.57
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 35}        max{col 51}= {res}    810.57

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 2}authvalues {c |}{col 14}{res}{space 2} 2.068988{col 26}{space 2} .0185982{col 37}{space 5} 2.032482{col 51}{space 3} 2.105494
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}
{res}{txt}
{com}. mi estimate: svy: mean selfest  
{res}
{txt}Multiple-imputation estimates{col 35}Imputations{col 51}= {res}        10
{txt}Survey: Mean estimation{col 35}Number of obs{col 51}= {res}     1,150

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 35}Population size{col 51}={res} 1,111.6712
{txt}{col 1}Number of PSUs{col 19}= {res}    1,150
{txt}{col 35}Average RVI{col 51}= {res}    0.0461
{txt}{col 35}Largest FMI{col 51}= {res}    0.0445
{txt}{col 35}Complete DF{col 51}= {res}      1149
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 35}DF:     min{col 51}= {res}    886.87
{txt}{col 35}        avg{col 51}= {res}    886.87
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 35}        max{col 51}= {res}    886.87

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 5}selfest {c |}{col 14}{res}{space 2}  .349129{col 26}{space 2} .0099739{col 37}{space 5} .3295537{col 51}{space 3} .3687043
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}
{res}{txt}
{com}. mi estimate: svy: mean GHblack
{res}
{txt}Multiple-imputation estimates{col 35}Imputations{col 51}= {res}        10
{txt}Survey: Mean estimation{col 35}Number of obs{col 51}= {res}     1,150

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 35}Population size{col 51}={res} 1,098.6393
{txt}{col 1}Number of PSUs{col 19}= {res}    1,150
{txt}{col 35}Average RVI{col 51}= {res}    0.0865
{txt}{col 35}Largest FMI{col 51}= {res}    0.0810
{txt}{col 35}Complete DF{col 51}= {res}      1149
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 35}DF:     min{col 51}= {res}    605.80
{txt}{col 35}        avg{col 51}= {res}    605.80
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 35}        max{col 51}= {res}    605.80

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 5}GHblack {c |}{col 14}{res}{space 2} 1.991353{col 26}{space 2} .0220122{col 37}{space 5} 1.948123{col 51}{space 3} 2.034582
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}
{res}{txt}
{com}. mi estimate: svy: mean GHMus
{res}
{txt}Multiple-imputation estimates{col 35}Imputations{col 51}= {res}        10
{txt}Survey: Mean estimation{col 35}Number of obs{col 51}= {res}     1,133

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 35}Population size{col 51}={res} 1,081.9584
{txt}{col 1}Number of PSUs{col 19}= {res}    1,133
{txt}{col 35}Average RVI{col 51}= {res}    0.0717
{txt}{col 35}Largest FMI{col 51}= {res}    0.0680
{txt}{col 35}Complete DF{col 51}= {res}      1132
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 35}DF:     min{col 51}= {res}    691.47
{txt}{col 35}        avg{col 51}= {res}    691.47
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 35}        max{col 51}= {res}    691.47

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 7}GHMus {c |}{col 14}{res}{space 2} 2.096359{col 26}{space 2} .0260154{col 37}{space 5} 2.045281{col 51}{space 3} 2.147438
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}
{res}{txt}
{com}. mi estimate: svy: mean GHEEur
{res}
{txt}Multiple-imputation estimates{col 35}Imputations{col 51}= {res}        10
{txt}Survey: Mean estimation{col 35}Number of obs{col 51}= {res}     1,130

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 35}Population size{col 51}={res} 1,079.6267
{txt}{col 1}Number of PSUs{col 19}= {res}    1,130
{txt}{col 35}Average RVI{col 51}= {res}    0.0295
{txt}{col 35}Largest FMI{col 51}= {res}    0.0289
{txt}{col 35}Complete DF{col 51}= {res}      1129
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 35}DF:     min{col 51}= {res}    995.51
{txt}{col 35}        avg{col 51}= {res}    995.51
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 35}        max{col 51}= {res}    995.51

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 6}GHEEur {c |}{col 14}{res}{space 2} 2.045792{col 26}{space 2}  .024378{col 37}{space 5} 1.997954{col 51}{space 3}  2.09363
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}
{res}{txt}
{com}. mi estimate: svy: mean GHwhite
{res}
{txt}Multiple-imputation estimates{col 35}Imputations{col 51}= {res}        10
{txt}Survey: Mean estimation{col 35}Number of obs{col 51}= {res}     1,178

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 35}Population size{col 51}={res} 1,130.1125
{txt}{col 1}Number of PSUs{col 19}= {res}    1,178
{txt}{col 35}Average RVI{col 51}= {res}    0.1454
{txt}{col 35}Largest FMI{col 51}= {res}    0.1303
{txt}{col 35}Complete DF{col 51}= {res}      1177
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 35}DF:     min{col 51}= {res}    361.52
{txt}{col 35}        avg{col 51}= {res}    361.52
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 35}        max{col 51}= {res}    361.52

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 5}GHwhite {c |}{col 14}{res}{space 2} 2.046767{col 26}{space 2} .0181635{col 37}{space 5} 2.011048{col 51}{space 3} 2.082487
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}
{res}{txt}
{com}. 
. * descriptives: minimum and maximum
. sum authvalues selfest GHblack GHMus GHEEur GHwhite 

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 2}authvalues {c |}{res}      9,104    2.067587    .6056404   .7169325          4
{txt}{space 5}selfest {c |}{res}      7,530     .348759    .2895307  -.3727047   1.227109
{txt}{space 5}GHblack {c |}{res}      7,565    1.978932     .618316    .561818   4.365032
{txt}{space 7}GHMus {c |}{res}      7,363    2.090653    .7390031   .5866538   4.221713
{txt}{space 6}GHEEur {c |}{res}      7,310    2.067331    .7064677   .4762756   4.021554
{txt}{hline 13}{c +}{hline 57}
{space 5}GHwhite {c |}{res}      7,921    2.051844    .5220702   .3098101      3.875
{txt}
{com}. 
. 
. *********************************************************************
. * TABLE A.7B IN THE APPENDIX:
. *       Predictors of Group Hostility under Decoupled Condition, 2016; 
. *       Threats Entered Individually
. * FIGURE 1 IN THE PAPER (2016 estimates):
. *       Unstandardized OLS Coefficient Estimates and 95% Confidence Intervals of the Impact of Threats
. *       on Group Hostility; Threats Entered Individually
. *       NOTE: for significance test of difference between 2011 and 2016 estimates, 
. **      see code for FIGURE 1 below 
. *********************************************************************
. 
. mi estimate: svy: reg GHblack threat1 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       967

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 924.759523
{txt}{col 1}Number of PSUs{col 19}= {res}      967
{txt}{col 49}Average RVI{col 67}= {res}    0.1003
{txt}{col 49}Largest FMI{col 67}= {res}    0.2685
{txt}{col 49}Complete DF{col 67}= {res}       966
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    114.23
{txt}{col 49}        avg{col 67}= {res}    615.97
{txt}{col 49}        max{col 67}= {res}    952.60
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  15{txt},{res}  908.2{txt}){col 67}= {res}     25.95
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           GHblack{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat1 {c |}{col 20}{res}{space 2} .0823392{col 32}{space 2} .0260398{col 43}{space 1}    3.16{col 52}{space 3}0.002{col 60}{space 4}  .031224{col 73}{space 3} .1334545
{txt}{space 12}female {c |}{col 20}{res}{space 2} -.084689{col 32}{space 2} .0406254{col 43}{space 1}   -2.08{col 52}{space 3}0.037{col 60}{space 4}-.1644548{col 73}{space 3}-.0049232
{txt}{space 15}Age {c |}{col 20}{res}{space 2} .0034281{col 32}{space 2} .0022061{col 43}{space 1}    1.55{col 52}{space 3}0.121{col 60}{space 4}-.0009051{col 73}{space 3} .0077612
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0238771{col 32}{space 2}  .013056{col 43}{space 1}   -1.83{col 52}{space 3}0.068{col 60}{space 4}-.0495056{col 73}{space 3} .0017513
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2} .0025239{col 32}{space 2} .0510556{col 43}{space 1}    0.05{col 52}{space 3}0.961{col 60}{space 4}-.0978118{col 73}{space 3} .1028597
{txt}{space 15}C2  {c |}{col 20}{res}{space 2} .0984673{col 32}{space 2} .0575224{col 43}{space 1}    1.71{col 52}{space 3}0.087{col 60}{space 4}-.0144447{col 73}{space 3} .2113792
{txt}{space 15}DE  {c |}{col 20}{res}{space 2} .0236729{col 32}{space 2} .0592482{col 43}{space 1}    0.40{col 52}{space 3}0.690{col 60}{space 4}-.0927482{col 73}{space 3} .1400941
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2} .0137131{col 32}{space 2} .0727876{col 43}{space 1}    0.19{col 52}{space 3}0.851{col 60}{space 4}-.1293852{col 73}{space 3} .1568114
{txt}full time student  {c |}{col 20}{res}{space 2}-.2851869{col 32}{space 2} .0862535{col 43}{space 1}   -3.31{col 52}{space 3}0.001{col 60}{space 4} -.454469{col 73}{space 3}-.1159047
{txt}{space 10}retired  {c |}{col 20}{res}{space 2}-.0078947{col 32}{space 2} .0709789{col 43}{space 1}   -0.11{col 52}{space 3}0.911{col 60}{space 4}-.1473062{col 73}{space 3} .1315167
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2}-.0840739{col 32}{space 2} .1629876{col 43}{space 1}   -0.52{col 52}{space 3}0.606{col 60}{space 4}-.4041189{col 73}{space 3} .2359712
{txt}{space 6}not working  {c |}{col 20}{res}{space 2} .0110775{col 32}{space 2} .0689044{col 43}{space 1}    0.16{col 52}{space 3}0.872{col 60}{space 4}-.1245643{col 73}{space 3} .1467192
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2}-.0894851{col 32}{space 2} .1888777{col 43}{space 1}   -0.47{col 52}{space 3}0.636{col 60}{space 4}-.4601495{col 73}{space 3} .2811794
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .4648073{col 32}{space 2}  .040783{col 43}{space 1}   11.40{col 52}{space 3}0.000{col 60}{space 4} .3847282{col 73}{space 3} .5448864
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .0833288{col 32}{space 2} .0888838{col 43}{space 1}    0.94{col 52}{space 3}0.350{col 60}{space 4}-.0927456{col 73}{space 3} .2594032
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 1.206478{col 32}{space 2} .3601593{col 43}{space 1}    3.35{col 52}{space 3}0.001{col 60}{space 4} .4994717{col 73}{space 3} 1.913484
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHblack threat2 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       952

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res}  907.66802
{txt}{col 1}Number of PSUs{col 19}= {res}      952
{txt}{col 49}Average RVI{col 67}= {res}    0.1102
{txt}{col 49}Largest FMI{col 67}= {res}    0.2678
{txt}{col 49}Complete DF{col 67}= {res}       951
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    114.47
{txt}{col 49}        avg{col 67}= {res}    570.53
{txt}{col 49}        max{col 67}= {res}    934.62
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  15{txt},{res}  884.3{txt}){col 67}= {res}     24.32
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           GHblack{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat2 {c |}{col 20}{res}{space 2}-.0122469{col 32}{space 2} .0269153{col 43}{space 1}   -0.46{col 52}{space 3}0.649{col 60}{space 4}-.0651389{col 73}{space 3}  .040645
{txt}{space 12}female {c |}{col 20}{res}{space 2}-.0718459{col 32}{space 2} .0410732{col 43}{space 1}   -1.75{col 52}{space 3}0.081{col 60}{space 4}-.1524951{col 73}{space 3} .0088032
{txt}{space 15}Age {c |}{col 20}{res}{space 2}  .003268{col 32}{space 2} .0022118{col 43}{space 1}    1.48{col 52}{space 3}0.140{col 60}{space 4}-.0010762{col 73}{space 3} .0076122
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0145175{col 32}{space 2} .0128301{col 43}{space 1}   -1.13{col 52}{space 3}0.258{col 60}{space 4}-.0397058{col 73}{space 3} .0106709
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2} .0044934{col 32}{space 2}  .051523{col 43}{space 1}    0.09{col 52}{space 3}0.931{col 60}{space 4}-.0967423{col 73}{space 3}  .105729
{txt}{space 15}C2  {c |}{col 20}{res}{space 2} .1033836{col 32}{space 2} .0568388{col 43}{space 1}    1.82{col 52}{space 3}0.069{col 60}{space 4}-.0081899{col 73}{space 3} .2149571
{txt}{space 15}DE  {c |}{col 20}{res}{space 2} .0366859{col 32}{space 2} .0594448{col 43}{space 1}    0.62{col 52}{space 3}0.537{col 60}{space 4}-.0801226{col 73}{space 3} .1534945
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2} .0128891{col 32}{space 2}  .070634{col 43}{space 1}    0.18{col 52}{space 3}0.855{col 60}{space 4}-.1260197{col 73}{space 3} .1517979
{txt}full time student  {c |}{col 20}{res}{space 2}-.2866437{col 32}{space 2} .0842549{col 43}{space 1}   -3.40{col 52}{space 3}0.001{col 60}{space 4}-.4520083{col 73}{space 3}-.1212791
{txt}{space 10}retired  {c |}{col 20}{res}{space 2} .0119072{col 32}{space 2}  .069452{col 43}{space 1}    0.17{col 52}{space 3}0.864{col 60}{space 4}-.1245429{col 73}{space 3} .1483573
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2}-.0391681{col 32}{space 2} .1616733{col 43}{space 1}   -0.24{col 52}{space 3}0.809{col 60}{space 4}-.3566544{col 73}{space 3} .2783182
{txt}{space 6}not working  {c |}{col 20}{res}{space 2} .0327215{col 32}{space 2}  .070267{col 43}{space 1}    0.47{col 52}{space 3}0.642{col 60}{space 4}-.1056852{col 73}{space 3} .1711283
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2}-.0692802{col 32}{space 2} .1988163{col 43}{space 1}   -0.35{col 52}{space 3}0.728{col 60}{space 4}-.4594583{col 73}{space 3} .3208978
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2}  .491094{col 32}{space 2} .0408932{col 43}{space 1}   12.01{col 52}{space 3}0.000{col 60}{space 4} .4107778{col 73}{space 3} .5714103
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .1767392{col 32}{space 2} .0860117{col 43}{space 1}    2.05{col 52}{space 3}0.042{col 60}{space 4} .0063581{col 73}{space 3} .3471202
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 1.136074{col 32}{space 2} .3698565{col 43}{space 1}    3.07{col 52}{space 3}0.002{col 60}{space 4}  .409928{col 73}{space 3}  1.86222
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHblack threat3 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       970

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 927.219308
{txt}{col 1}Number of PSUs{col 19}= {res}      970
{txt}{col 49}Average RVI{col 67}= {res}    0.1000
{txt}{col 49}Largest FMI{col 67}= {res}    0.2513
{txt}{col 49}Complete DF{col 67}= {res}       969
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    127.71
{txt}{col 49}        avg{col 67}= {res}    625.71
{txt}{col 49}        max{col 67}= {res}    956.24
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  15{txt},{res}  911.7{txt}){col 67}= {res}     25.54
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           GHblack{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat3 {c |}{col 20}{res}{space 2} .0900477{col 32}{space 2}  .025389{col 43}{space 1}    3.55{col 52}{space 3}0.000{col 60}{space 4} .0402207{col 73}{space 3} .1398746
{txt}{space 12}female {c |}{col 20}{res}{space 2}-.0992367{col 32}{space 2} .0405454{col 43}{space 1}   -2.45{col 52}{space 3}0.015{col 60}{space 4}-.1788405{col 73}{space 3}-.0196329
{txt}{space 15}Age {c |}{col 20}{res}{space 2} .0035169{col 32}{space 2} .0021726{col 43}{space 1}    1.62{col 52}{space 3}0.106{col 60}{space 4}-.0007504{col 73}{space 3} .0077842
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0216913{col 32}{space 2} .0130378{col 43}{space 1}   -1.66{col 52}{space 3}0.097{col 60}{space 4}-.0472839{col 73}{space 3} .0039014
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2} .0084299{col 32}{space 2} .0514445{col 43}{space 1}    0.16{col 52}{space 3}0.870{col 60}{space 4}-.0926622{col 73}{space 3} .1095221
{txt}{space 15}C2  {c |}{col 20}{res}{space 2} .1074503{col 32}{space 2} .0568513{col 43}{space 1}    1.89{col 52}{space 3}0.059{col 60}{space 4}-.0041415{col 73}{space 3} .2190422
{txt}{space 15}DE  {c |}{col 20}{res}{space 2} .0371681{col 32}{space 2} .0574947{col 43}{space 1}    0.65{col 52}{space 3}0.518{col 60}{space 4}-.0757984{col 73}{space 3} .1501345
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2} .0104384{col 32}{space 2} .0713435{col 43}{space 1}    0.15{col 52}{space 3}0.884{col 60}{space 4}-.1298279{col 73}{space 3} .1507046
{txt}full time student  {c |}{col 20}{res}{space 2}-.2863349{col 32}{space 2} .0838765{col 43}{space 1}   -3.41{col 52}{space 3}0.001{col 60}{space 4}-.4509545{col 73}{space 3}-.1217153
{txt}{space 10}retired  {c |}{col 20}{res}{space 2}-.0149612{col 32}{space 2} .0707907{col 43}{space 1}   -0.21{col 52}{space 3}0.833{col 60}{space 4}-.1540015{col 73}{space 3} .1240792
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2}-.0887308{col 32}{space 2} .1616027{col 43}{space 1}   -0.55{col 52}{space 3}0.583{col 60}{space 4}-.4060576{col 73}{space 3}  .228596
{txt}{space 6}not working  {c |}{col 20}{res}{space 2}  .005964{col 32}{space 2} .0682791{col 43}{space 1}    0.09{col 52}{space 3}0.930{col 60}{space 4}-.1284637{col 73}{space 3} .1403917
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2}-.0928768{col 32}{space 2} .1914932{col 43}{space 1}   -0.49{col 52}{space 3}0.628{col 60}{space 4}-.4686721{col 73}{space 3} .2829186
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .4712768{col 32}{space 2} .0402689{col 43}{space 1}   11.70{col 52}{space 3}0.000{col 60}{space 4} .3922035{col 73}{space 3}   .55035
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .1074299{col 32}{space 2} .0846856{col 43}{space 1}    1.27{col 52}{space 3}0.207{col 60}{space 4}-.0601387{col 73}{space 3} .2749985
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 1.079159{col 32}{space 2} .3706981{col 43}{space 1}    2.91{col 52}{space 3}0.004{col 60}{space 4} .3514223{col 73}{space 3} 1.806896
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHblack threat4 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       964

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 921.366236
{txt}{col 1}Number of PSUs{col 19}= {res}      964
{txt}{col 49}Average RVI{col 67}= {res}    0.1132
{txt}{col 49}Largest FMI{col 67}= {res}    0.2770
{txt}{col 49}Complete DF{col 67}= {res}       963
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    108.30
{txt}{col 49}        avg{col 67}= {res}    577.93
{txt}{col 49}        max{col 67}= {res}    949.52
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  15{txt},{res}  894.8{txt}){col 67}= {res}     33.70
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           GHblack{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat4 {c |}{col 20}{res}{space 2} .2060689{col 32}{space 2} .0242283{col 43}{space 1}    8.51{col 52}{space 3}0.000{col 60}{space 4} .1584578{col 73}{space 3}   .25368
{txt}{space 12}female {c |}{col 20}{res}{space 2}-.1004425{col 32}{space 2} .0386146{col 43}{space 1}   -2.60{col 52}{space 3}0.009{col 60}{space 4}-.1762642{col 73}{space 3}-.0246209
{txt}{space 15}Age {c |}{col 20}{res}{space 2} .0005949{col 32}{space 2} .0020918{col 43}{space 1}    0.28{col 52}{space 3}0.776{col 60}{space 4}-.0035154{col 73}{space 3} .0047053
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0080581{col 32}{space 2}  .012811{col 43}{space 1}   -0.63{col 52}{space 3}0.530{col 60}{space 4}-.0332051{col 73}{space 3}  .017089
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2}-.0366445{col 32}{space 2} .0501688{col 43}{space 1}   -0.73{col 52}{space 3}0.466{col 60}{space 4}-.1352697{col 73}{space 3} .0619806
{txt}{space 15}C2  {c |}{col 20}{res}{space 2} .0605128{col 32}{space 2} .0544666{col 43}{space 1}    1.11{col 52}{space 3}0.267{col 60}{space 4}-.0464059{col 73}{space 3} .1674315
{txt}{space 15}DE  {c |}{col 20}{res}{space 2} .0059449{col 32}{space 2} .0546137{col 43}{space 1}    0.11{col 52}{space 3}0.913{col 60}{space 4}-.1013637{col 73}{space 3} .1132536
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2} .0231404{col 32}{space 2}  .070112{col 43}{space 1}    0.33{col 52}{space 3}0.742{col 60}{space 4}-.1147448{col 73}{space 3} .1610255
{txt}full time student  {c |}{col 20}{res}{space 2}-.2473827{col 32}{space 2}  .082857{col 43}{space 1}   -2.99{col 52}{space 3}0.003{col 60}{space 4} -.410002{col 73}{space 3}-.0847634
{txt}{space 10}retired  {c |}{col 20}{res}{space 2} .0106487{col 32}{space 2} .0667699{col 43}{space 1}    0.16{col 52}{space 3}0.873{col 60}{space 4}-.1205183{col 73}{space 3} .1418158
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2}-.0931294{col 32}{space 2} .1568782{col 43}{space 1}   -0.59{col 52}{space 3}0.553{col 60}{space 4}-.4011735{col 73}{space 3} .2149147
{txt}{space 6}not working  {c |}{col 20}{res}{space 2}-.0262562{col 32}{space 2} .0654721{col 43}{space 1}   -0.40{col 52}{space 3}0.689{col 60}{space 4}-.1552394{col 73}{space 3} .1027271
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2}-.0862535{col 32}{space 2} .1568253{col 43}{space 1}   -0.55{col 52}{space 3}0.582{col 60}{space 4}-.3940177{col 73}{space 3} .2215106
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .3818123{col 32}{space 2} .0414337{col 43}{space 1}    9.22{col 52}{space 3}0.000{col 60}{space 4} .3004565{col 73}{space 3} .4631681
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .0759345{col 32}{space 2} .0823844{col 43}{space 1}    0.92{col 52}{space 3}0.359{col 60}{space 4}-.0873606{col 73}{space 3} .2392296
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} .8820973{col 32}{space 2} .3424648{col 43}{space 1}    2.58{col 52}{space 3}0.010{col 60}{space 4} .2098432{col 73}{space 3} 1.554351
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHblack threat5 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       954

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 911.188513
{txt}{col 1}Number of PSUs{col 19}= {res}      954
{txt}{col 49}Average RVI{col 67}= {res}    0.1020
{txt}{col 49}Largest FMI{col 67}= {res}    0.2569
{txt}{col 49}Complete DF{col 67}= {res}       953
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    122.75
{txt}{col 49}        avg{col 67}= {res}    595.72
{txt}{col 49}        max{col 67}= {res}    939.87
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  15{txt},{res}  894.4{txt}){col 67}= {res}     24.56
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           GHblack{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat5 {c |}{col 20}{res}{space 2} -.036425{col 32}{space 2} .0255806{col 43}{space 1}   -1.42{col 52}{space 3}0.155{col 60}{space 4}-.0866507{col 73}{space 3} .0138008
{txt}{space 12}female {c |}{col 20}{res}{space 2} -.080248{col 32}{space 2} .0414523{col 43}{space 1}   -1.94{col 52}{space 3}0.053{col 60}{space 4}-.1616523{col 73}{space 3} .0011563
{txt}{space 15}Age {c |}{col 20}{res}{space 2}  .003414{col 32}{space 2} .0022214{col 43}{space 1}    1.54{col 52}{space 3}0.125{col 60}{space 4}-.0009491{col 73}{space 3}  .007777
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0187022{col 32}{space 2} .0132157{col 43}{space 1}   -1.42{col 52}{space 3}0.157{col 60}{space 4}-.0446451{col 73}{space 3} .0072406
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2} .0129153{col 32}{space 2} .0519487{col 43}{space 1}    0.25{col 52}{space 3}0.804{col 60}{space 4} -.089173{col 73}{space 3} .1150036
{txt}{space 15}C2  {c |}{col 20}{res}{space 2} .1075947{col 32}{space 2}  .057739{col 43}{space 1}    1.86{col 52}{space 3}0.063{col 60}{space 4}-.0057399{col 73}{space 3} .2209292
{txt}{space 15}DE  {c |}{col 20}{res}{space 2} .0435494{col 32}{space 2} .0592477{col 43}{space 1}    0.74{col 52}{space 3}0.463{col 60}{space 4}-.0728572{col 73}{space 3}  .159956
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2}-.0028599{col 32}{space 2}  .071112{col 43}{space 1}   -0.04{col 52}{space 3}0.968{col 60}{space 4}-.1426751{col 73}{space 3} .1369553
{txt}full time student  {c |}{col 20}{res}{space 2}-.2960803{col 32}{space 2} .0833665{col 43}{space 1}   -3.55{col 52}{space 3}0.000{col 60}{space 4}-.4597013{col 73}{space 3}-.1324593
{txt}{space 10}retired  {c |}{col 20}{res}{space 2}-.0111908{col 32}{space 2}  .071506{col 43}{space 1}   -0.16{col 52}{space 3}0.876{col 60}{space 4}-.1516451{col 73}{space 3} .1292634
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2}-.0553336{col 32}{space 2} .1640634{col 43}{space 1}   -0.34{col 52}{space 3}0.736{col 60}{space 4}-.3774915{col 73}{space 3} .2668243
{txt}{space 6}not working  {c |}{col 20}{res}{space 2} .0056802{col 32}{space 2} .0712331{col 43}{space 1}    0.08{col 52}{space 3}0.937{col 60}{space 4}-.1345695{col 73}{space 3}   .14593
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2}-.0768189{col 32}{space 2} .1789768{col 43}{space 1}   -0.43{col 52}{space 3}0.668{col 60}{space 4}-.4280593{col 73}{space 3} .2744215
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .4700478{col 32}{space 2} .0414927{col 43}{space 1}   11.33{col 52}{space 3}0.000{col 60}{space 4} .3885515{col 73}{space 3} .5515442
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .1515072{col 32}{space 2} .0874266{col 43}{space 1}    1.73{col 52}{space 3}0.086{col 60}{space 4}-.0215518{col 73}{space 3} .3245662
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 1.345907{col 32}{space 2} .3677648{col 43}{space 1}    3.66{col 52}{space 3}0.000{col 60}{space 4} .6239025{col 73}{space 3} 2.067912
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. mi estimate: svy: reg GHMus threat1 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       966

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res}  923.86943
{txt}{col 1}Number of PSUs{col 19}= {res}      966
{txt}{col 49}Average RVI{col 67}= {res}    0.0854
{txt}{col 49}Largest FMI{col 67}= {res}    0.1514
{txt}{col 49}Complete DF{col 67}= {res}       965
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    276.19
{txt}{col 49}        avg{col 67}= {res}    655.20
{txt}{col 49}        max{col 67}= {res}    917.55
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  15{txt},{res}  920.5{txt}){col 67}= {res}     28.07
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}             GHMus{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat1 {c |}{col 20}{res}{space 2} .0875751{col 32}{space 2} .0290151{col 43}{space 1}    3.02{col 52}{space 3}0.003{col 60}{space 4} .0306155{col 73}{space 3} .1445346
{txt}{space 12}female {c |}{col 20}{res}{space 2}-.0926303{col 32}{space 2} .0462257{col 43}{space 1}   -2.00{col 52}{space 3}0.045{col 60}{space 4} -.183378{col 73}{space 3}-.0018826
{txt}{space 15}Age {c |}{col 20}{res}{space 2} .0050041{col 32}{space 2} .0022097{col 43}{space 1}    2.26{col 52}{space 3}0.024{col 60}{space 4} .0006665{col 73}{space 3} .0093418
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0537329{col 32}{space 2} .0139587{col 43}{space 1}   -3.85{col 52}{space 3}0.000{col 60}{space 4}-.0811414{col 73}{space 3}-.0263244
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2} .0311272{col 32}{space 2} .0519016{col 43}{space 1}    0.60{col 52}{space 3}0.549{col 60}{space 4}-.0707759{col 73}{space 3} .1330302
{txt}{space 15}C2  {c |}{col 20}{res}{space 2} .1540952{col 32}{space 2} .0657892{col 43}{space 1}    2.34{col 52}{space 3}0.019{col 60}{space 4} .0249439{col 73}{space 3} .2832466
{txt}{space 15}DE  {c |}{col 20}{res}{space 2} .0372959{col 32}{space 2} .0715785{col 43}{space 1}    0.52{col 52}{space 3}0.603{col 60}{space 4}-.1033589{col 73}{space 3} .1779507
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2} .0052474{col 32}{space 2} .0740867{col 43}{space 1}    0.07{col 52}{space 3}0.944{col 60}{space 4}-.1401827{col 73}{space 3} .1506775
{txt}full time student  {c |}{col 20}{res}{space 2}-.2913078{col 32}{space 2} .0966519{col 43}{space 1}   -3.01{col 52}{space 3}0.003{col 60}{space 4} -.480996{col 73}{space 3}-.1016196
{txt}{space 10}retired  {c |}{col 20}{res}{space 2} -.048376{col 32}{space 2} .0735596{col 43}{space 1}   -0.66{col 52}{space 3}0.511{col 60}{space 4}-.1927785{col 73}{space 3} .0960265
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2} .3630958{col 32}{space 2} .1721934{col 43}{space 1}    2.11{col 52}{space 3}0.035{col 60}{space 4} .0250635{col 73}{space 3}  .701128
{txt}{space 6}not working  {c |}{col 20}{res}{space 2} .1283497{col 32}{space 2} .0890212{col 43}{space 1}    1.44{col 52}{space 3}0.150{col 60}{space 4}-.0467832{col 73}{space 3} .3034826
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2}-.2913315{col 32}{space 2} .1991378{col 43}{space 1}   -1.46{col 52}{space 3}0.144{col 60}{space 4}-.6821499{col 73}{space 3}  .099487
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .4637289{col 32}{space 2} .0466396{col 43}{space 1}    9.94{col 52}{space 3}0.000{col 60}{space 4} .3719391{col 73}{space 3} .5555186
{txt}{space 11}selfest {c |}{col 20}{res}{space 2}  .188332{col 32}{space 2} .0898997{col 43}{space 1}    2.09{col 52}{space 3}0.037{col 60}{space 4} .0113563{col 73}{space 3} .3653077
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 1.882071{col 32}{space 2} .3832081{col 43}{space 1}    4.91{col 52}{space 3}0.000{col 60}{space 4} 1.129415{col 73}{space 3} 2.634726
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHMus threat2 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       950

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 907.393918
{txt}{col 1}Number of PSUs{col 19}= {res}      950
{txt}{col 49}Average RVI{col 67}= {res}    0.0889
{txt}{col 49}Largest FMI{col 67}= {res}    0.1550
{txt}{col 49}Complete DF{col 67}= {res}       949
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    265.99
{txt}{col 49}        avg{col 67}= {res}    634.45
{txt}{col 49}        max{col 67}= {res}    901.24
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  15{txt},{res}  903.4{txt}){col 67}= {res}     27.36
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}             GHMus{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat2 {c |}{col 20}{res}{space 2}-.0574661{col 32}{space 2} .0300495{col 43}{space 1}   -1.91{col 52}{space 3}0.056{col 60}{space 4}-.1164721{col 73}{space 3} .0015399
{txt}{space 12}female {c |}{col 20}{res}{space 2}-.0790466{col 32}{space 2} .0466858{col 43}{space 1}   -1.69{col 52}{space 3}0.091{col 60}{space 4}-.1706968{col 73}{space 3} .0126036
{txt}{space 15}Age {c |}{col 20}{res}{space 2} .0045239{col 32}{space 2} .0022516{col 43}{space 1}    2.01{col 52}{space 3}0.045{col 60}{space 4} .0001037{col 73}{space 3}  .008944
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0472735{col 32}{space 2} .0142307{col 43}{space 1}   -3.32{col 52}{space 3}0.001{col 60}{space 4}-.0752189{col 73}{space 3}-.0193281
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2} .0460375{col 32}{space 2} .0530424{col 43}{space 1}    0.87{col 52}{space 3}0.386{col 60}{space 4}-.0581035{col 73}{space 3} .1501785
{txt}{space 15}C2  {c |}{col 20}{res}{space 2}  .173588{col 32}{space 2} .0660079{col 43}{space 1}    2.63{col 52}{space 3}0.009{col 60}{space 4} .0439943{col 73}{space 3} .3031816
{txt}{space 15}DE  {c |}{col 20}{res}{space 2} .0772602{col 32}{space 2} .0723384{col 43}{space 1}    1.07{col 52}{space 3}0.286{col 60}{space 4}-.0649055{col 73}{space 3} .2194259
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2}-.0130938{col 32}{space 2} .0732471{col 43}{space 1}   -0.18{col 52}{space 3}0.858{col 60}{space 4}-.1568794{col 73}{space 3} .1306917
{txt}full time student  {c |}{col 20}{res}{space 2}-.2693249{col 32}{space 2} .0960623{col 43}{space 1}   -2.80{col 52}{space 3}0.005{col 60}{space 4}-.4578611{col 73}{space 3}-.0807887
{txt}{space 10}retired  {c |}{col 20}{res}{space 2} -.044014{col 32}{space 2} .0740663{col 43}{space 1}   -0.59{col 52}{space 3}0.553{col 60}{space 4}-.1894208{col 73}{space 3} .1013927
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2} .3952775{col 32}{space 2} .1800006{col 43}{space 1}    2.20{col 52}{space 3}0.028{col 60}{space 4} .0419343{col 73}{space 3} .7486207
{txt}{space 6}not working  {c |}{col 20}{res}{space 2} .1422318{col 32}{space 2} .0890443{col 43}{space 1}    1.60{col 52}{space 3}0.111{col 60}{space 4}-.0329846{col 73}{space 3} .3174483
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2}-.2735962{col 32}{space 2} .2141344{col 43}{space 1}   -1.28{col 52}{space 3}0.202{col 60}{space 4}-.6938562{col 73}{space 3} .1466639
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2}   .47951{col 32}{space 2} .0477287{col 43}{space 1}   10.05{col 52}{space 3}0.000{col 60}{space 4} .3855772{col 73}{space 3} .5734428
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .2957542{col 32}{space 2}  .092663{col 43}{space 1}    3.19{col 52}{space 3}0.002{col 60}{space 4} .1133079{col 73}{space 3} .4782005
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 2.033692{col 32}{space 2} .4101664{col 43}{space 1}    4.96{col 52}{space 3}0.000{col 60}{space 4} 1.228066{col 73}{space 3} 2.839318
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHMus threat3 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       967

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 924.689356
{txt}{col 1}Number of PSUs{col 19}= {res}      967
{txt}{col 49}Average RVI{col 67}= {res}    0.0849
{txt}{col 49}Largest FMI{col 67}= {res}    0.1454
{txt}{col 49}Complete DF{col 67}= {res}       966
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    291.78
{txt}{col 49}        avg{col 67}= {res}    662.66
{txt}{col 49}        max{col 67}= {res}    916.36
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  15{txt},{res}  922.1{txt}){col 67}= {res}     27.35
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}             GHMus{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat3 {c |}{col 20}{res}{space 2} .0566801{col 32}{space 2} .0281541{col 43}{space 1}    2.01{col 52}{space 3}0.044{col 60}{space 4} .0014148{col 73}{space 3} .1119453
{txt}{space 12}female {c |}{col 20}{res}{space 2}-.0965155{col 32}{space 2} .0463199{col 43}{space 1}   -2.08{col 52}{space 3}0.038{col 60}{space 4}-.1874455{col 73}{space 3}-.0055855
{txt}{space 15}Age {c |}{col 20}{res}{space 2} .0050788{col 32}{space 2} .0022161{col 43}{space 1}    2.29{col 52}{space 3}0.022{col 60}{space 4} .0007287{col 73}{space 3} .0094288
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0509768{col 32}{space 2} .0139651{col 43}{space 1}   -3.65{col 52}{space 3}0.000{col 60}{space 4}-.0783981{col 73}{space 3}-.0235555
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2} .0366708{col 32}{space 2} .0524069{col 43}{space 1}    0.70{col 52}{space 3}0.484{col 60}{space 4}-.0662201{col 73}{space 3} .1395618
{txt}{space 15}C2  {c |}{col 20}{res}{space 2} .1647492{col 32}{space 2}  .065915{col 43}{space 1}    2.50{col 52}{space 3}0.013{col 60}{space 4}  .035345{col 73}{space 3} .2941535
{txt}{space 15}DE  {c |}{col 20}{res}{space 2} .0618261{col 32}{space 2}  .070733{col 43}{space 1}    0.87{col 52}{space 3}0.383{col 60}{space 4} -.077177{col 73}{space 3} .2008292
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2}-.0027083{col 32}{space 2} .0734695{col 43}{space 1}   -0.04{col 52}{space 3}0.971{col 60}{space 4}-.1469235{col 73}{space 3} .1415069
{txt}full time student  {c |}{col 20}{res}{space 2}-.2689259{col 32}{space 2} .0987753{col 43}{space 1}   -2.72{col 52}{space 3}0.007{col 60}{space 4}-.4627803{col 73}{space 3}-.0750716
{txt}{space 10}retired  {c |}{col 20}{res}{space 2}-.0567126{col 32}{space 2} .0738976{col 43}{space 1}   -0.77{col 52}{space 3}0.443{col 60}{space 4}-.2017771{col 73}{space 3} .0883519
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2} .3693824{col 32}{space 2} .1778315{col 43}{space 1}    2.08{col 52}{space 3}0.038{col 60}{space 4}  .020299{col 73}{space 3} .7184658
{txt}{space 6}not working  {c |}{col 20}{res}{space 2} .1211514{col 32}{space 2} .0882561{col 43}{space 1}    1.37{col 52}{space 3}0.171{col 60}{space 4}-.0524813{col 73}{space 3} .2947841
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2}-.2914512{col 32}{space 2} .1987696{col 43}{space 1}   -1.47{col 52}{space 3}0.143{col 60}{space 4}-.6815477{col 73}{space 3} .0986453
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .4793768{col 32}{space 2} .0467365{col 43}{space 1}   10.26{col 52}{space 3}0.000{col 60}{space 4} .3873935{col 73}{space 3} .5713601
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .2319423{col 32}{space 2} .0878246{col 43}{space 1}    2.64{col 52}{space 3}0.009{col 60}{space 4} .0591015{col 73}{space 3} .4047831
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 1.815778{col 32}{space 2} .3971915{col 43}{space 1}    4.57{col 52}{space 3}0.000{col 60}{space 4} 1.035734{col 73}{space 3} 2.595822
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHMus threat4 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       961

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 918.765172
{txt}{col 1}Number of PSUs{col 19}= {res}      961
{txt}{col 49}Average RVI{col 67}= {res}    0.0944
{txt}{col 49}Largest FMI{col 67}= {res}    0.1583
{txt}{col 49}Complete DF{col 67}= {res}       960
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    259.51
{txt}{col 49}        avg{col 67}= {res}    618.30
{txt}{col 49}        max{col 67}= {res}    884.68
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  15{txt},{res}  909.0{txt}){col 67}= {res}     40.98
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}             GHMus{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat4 {c |}{col 20}{res}{space 2} .2505222{col 32}{space 2}  .026823{col 43}{space 1}    9.34{col 52}{space 3}0.000{col 60}{space 4} .1978029{col 73}{space 3} .3032416
{txt}{space 12}female {c |}{col 20}{res}{space 2}-.1091665{col 32}{space 2} .0438832{col 43}{space 1}   -2.49{col 52}{space 3}0.013{col 60}{space 4}-.1953329{col 73}{space 3}-.0230001
{txt}{space 15}Age {c |}{col 20}{res}{space 2} .0018473{col 32}{space 2} .0020371{col 43}{space 1}    0.91{col 52}{space 3}0.365{col 60}{space 4}-.0021515{col 73}{space 3}  .005846
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2} -.032039{col 32}{space 2} .0135991{col 43}{space 1}   -2.36{col 52}{space 3}0.019{col 60}{space 4}-.0587448{col 73}{space 3}-.0053333
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2}-.0092819{col 32}{space 2} .0508202{col 43}{space 1}   -0.18{col 52}{space 3}0.855{col 60}{space 4}  -.10907{col 73}{space 3} .0905062
{txt}{space 15}C2  {c |}{col 20}{res}{space 2} .1078004{col 32}{space 2} .0601052{col 43}{space 1}    1.79{col 52}{space 3}0.073{col 60}{space 4}-.0102016{col 73}{space 3} .2258025
{txt}{space 15}DE  {c |}{col 20}{res}{space 2} .0268471{col 32}{space 2} .0664976{col 43}{space 1}    0.40{col 52}{space 3}0.687{col 60}{space 4}-.1038521{col 73}{space 3} .1575463
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2} .0127371{col 32}{space 2} .0698603{col 43}{space 1}    0.18{col 52}{space 3}0.855{col 60}{space 4}-.1244027{col 73}{space 3}  .149877
{txt}full time student  {c |}{col 20}{res}{space 2}-.2301339{col 32}{space 2} .0888387{col 43}{space 1}   -2.59{col 52}{space 3}0.010{col 60}{space 4}-.4044931{col 73}{space 3}-.0557748
{txt}{space 10}retired  {c |}{col 20}{res}{space 2}-.0313166{col 32}{space 2} .0675606{col 43}{space 1}   -0.46{col 52}{space 3}0.643{col 60}{space 4}-.1639392{col 73}{space 3}  .101306
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2} .2816002{col 32}{space 2} .1632557{col 43}{space 1}    1.72{col 52}{space 3}0.085{col 60}{space 4}-.0388624{col 73}{space 3} .6020628
{txt}{space 6}not working  {c |}{col 20}{res}{space 2}  .081272{col 32}{space 2} .0858312{col 43}{space 1}    0.95{col 52}{space 3}0.344{col 60}{space 4}  -.08767{col 73}{space 3} .2502141
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2}-.2870472{col 32}{space 2} .1552273{col 43}{space 1}   -1.85{col 52}{space 3}0.065{col 60}{space 4}-.5917087{col 73}{space 3} .0176142
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .3635088{col 32}{space 2} .0476693{col 43}{space 1}    7.63{col 52}{space 3}0.000{col 60}{space 4} .2697008{col 73}{space 3} .4573168
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .1608032{col 32}{space 2} .0841804{col 43}{space 1}    1.91{col 52}{space 3}0.057{col 60}{space 4}-.0049605{col 73}{space 3} .3265669
{txt}{space 13}_cons {c |}{col 20}{res}{space 2}  1.40248{col 32}{space 2} .3560724{col 43}{space 1}    3.94{col 52}{space 3}0.000{col 60}{space 4} .7032029{col 73}{space 3} 2.101757
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHMus threat5 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest 
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       953

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 910.761501
{txt}{col 1}Number of PSUs{col 19}= {res}      953
{txt}{col 49}Average RVI{col 67}= {res}    0.0870
{txt}{col 49}Largest FMI{col 67}= {res}    0.1570
{txt}{col 49}Complete DF{col 67}= {res}       952
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    261.70
{txt}{col 49}        avg{col 67}= {res}    650.38
{txt}{col 49}        max{col 67}= {res}    897.13
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  15{txt},{res}  908.4{txt}){col 67}= {res}     29.38
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}             GHMus{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat5 {c |}{col 20}{res}{space 2}-.1025523{col 32}{space 2} .0281662{col 43}{space 1}   -3.64{col 52}{space 3}0.000{col 60}{space 4}-.1578352{col 73}{space 3}-.0472694
{txt}{space 12}female {c |}{col 20}{res}{space 2}-.0807016{col 32}{space 2} .0460406{col 43}{space 1}   -1.75{col 52}{space 3}0.080{col 60}{space 4}-.1710865{col 73}{space 3} .0096833
{txt}{space 15}Age {c |}{col 20}{res}{space 2}  .003932{col 32}{space 2} .0022747{col 43}{space 1}    1.73{col 52}{space 3}0.084{col 60}{space 4}-.0005333{col 73}{space 3} .0083973
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0431931{col 32}{space 2} .0141098{col 43}{space 1}   -3.06{col 52}{space 3}0.002{col 60}{space 4}-.0709018{col 73}{space 3}-.0154845
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2} .0279643{col 32}{space 2} .0525462{col 43}{space 1}    0.53{col 52}{space 3}0.595{col 60}{space 4} -.075207{col 73}{space 3} .1311356
{txt}{space 15}C2  {c |}{col 20}{res}{space 2} .1575871{col 32}{space 2} .0643222{col 43}{space 1}    2.45{col 52}{space 3}0.015{col 60}{space 4} .0313077{col 73}{space 3} .2838665
{txt}{space 15}DE  {c |}{col 20}{res}{space 2} .0681311{col 32}{space 2} .0710623{col 43}{space 1}    0.96{col 52}{space 3}0.338{col 60}{space 4}-.0715165{col 73}{space 3} .2077786
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2}-.0158718{col 32}{space 2} .0723162{col 43}{space 1}   -0.22{col 52}{space 3}0.826{col 60}{space 4}-.1578291{col 73}{space 3} .1260854
{txt}full time student  {c |}{col 20}{res}{space 2}-.2607369{col 32}{space 2} .0936393{col 43}{space 1}   -2.78{col 52}{space 3}0.005{col 60}{space 4}-.4445177{col 73}{space 3}-.0769561
{txt}{space 10}retired  {c |}{col 20}{res}{space 2}-.0474134{col 32}{space 2} .0731305{col 43}{space 1}   -0.65{col 52}{space 3}0.517{col 60}{space 4}-.1909796{col 73}{space 3} .0961527
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2} .3886183{col 32}{space 2} .1751501{col 43}{space 1}    2.22{col 52}{space 3}0.027{col 60}{space 4} .0448006{col 73}{space 3} .7324361
{txt}{space 6}not working  {c |}{col 20}{res}{space 2} .1205569{col 32}{space 2} .0887995{col 43}{space 1}    1.36{col 52}{space 3}0.176{col 60}{space 4}-.0541501{col 73}{space 3} .2952639
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2}-.2693434{col 32}{space 2} .1914477{col 43}{space 1}   -1.41{col 52}{space 3}0.160{col 60}{space 4}-.6450808{col 73}{space 3} .1063941
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .4584419{col 32}{space 2} .0478407{col 43}{space 1}    9.58{col 52}{space 3}0.000{col 60}{space 4} .3642843{col 73}{space 3} .5525995
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .2789781{col 32}{space 2} .0900636{col 43}{space 1}    3.10{col 52}{space 3}0.002{col 60}{space 4} .1016366{col 73}{space 3} .4563197
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 2.168985{col 32}{space 2} .3974164{col 43}{space 1}    5.46{col 52}{space 3}0.000{col 60}{space 4} 1.388416{col 73}{space 3} 2.949554
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. mi estimate: svy: reg GHEEur threat1 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       964

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res}  925.17036
{txt}{col 1}Number of PSUs{col 19}= {res}      964
{txt}{col 49}Average RVI{col 67}= {res}    0.0990
{txt}{col 49}Largest FMI{col 67}= {res}    0.1867
{txt}{col 49}Complete DF{col 67}= {res}       963
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    204.57
{txt}{col 49}        avg{col 67}= {res}    553.60
{txt}{col 49}        max{col 67}= {res}    957.38
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  15{txt},{res}  900.8{txt}){col 67}= {res}     31.67
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}            GHEEur{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat1 {c |}{col 20}{res}{space 2}  .066469{col 32}{space 2}  .026513{col 43}{space 1}    2.51{col 52}{space 3}0.012{col 60}{space 4}  .014411{col 73}{space 3} .1185269
{txt}{space 12}female {c |}{col 20}{res}{space 2}-.0133758{col 32}{space 2} .0432433{col 43}{space 1}   -0.31{col 52}{space 3}0.757{col 60}{space 4} -.098342{col 73}{space 3} .0715905
{txt}{space 15}Age {c |}{col 20}{res}{space 2} .0020969{col 32}{space 2} .0021506{col 43}{space 1}    0.98{col 52}{space 3}0.330{col 60}{space 4}-.0021288{col 73}{space 3} .0063226
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0711696{col 32}{space 2} .0142301{col 43}{space 1}   -5.00{col 52}{space 3}0.000{col 60}{space 4} -.099124{col 73}{space 3}-.0432152
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2} .0128402{col 32}{space 2} .0514606{col 43}{space 1}    0.25{col 52}{space 3}0.803{col 60}{space 4}-.0883938{col 73}{space 3} .1140741
{txt}{space 15}C2  {c |}{col 20}{res}{space 2} .0579474{col 32}{space 2} .0675561{col 43}{space 1}    0.86{col 52}{space 3}0.392{col 60}{space 4}-.0749635{col 73}{space 3} .1908584
{txt}{space 15}DE  {c |}{col 20}{res}{space 2} .1041829{col 32}{space 2} .0655941{col 43}{space 1}    1.59{col 52}{space 3}0.113{col 60}{space 4}-.0248052{col 73}{space 3} .2331709
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2} -.085272{col 32}{space 2} .0707894{col 43}{space 1}   -1.20{col 52}{space 3}0.229{col 60}{space 4}-.2242257{col 73}{space 3} .0536817
{txt}full time student  {c |}{col 20}{res}{space 2}-.3221071{col 32}{space 2} .0876589{col 43}{space 1}   -3.67{col 52}{space 3}0.000{col 60}{space 4}-.4941808{col 73}{space 3}-.1500334
{txt}{space 10}retired  {c |}{col 20}{res}{space 2} .0412187{col 32}{space 2} .0686706{col 43}{space 1}    0.60{col 52}{space 3}0.549{col 60}{space 4}-.0937338{col 73}{space 3} .1761711
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2} .3532794{col 32}{space 2} .1870722{col 43}{space 1}    1.89{col 52}{space 3}0.059{col 60}{space 4}-.0139071{col 73}{space 3} .7204659
{txt}{space 6}not working  {c |}{col 20}{res}{space 2} .0584363{col 32}{space 2} .0864358{col 43}{space 1}    0.68{col 52}{space 3}0.499{col 60}{space 4}-.1116072{col 73}{space 3} .2284799
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2}-.3316749{col 32}{space 2} .2256907{col 43}{space 1}   -1.47{col 52}{space 3}0.142{col 60}{space 4}-.7745804{col 73}{space 3} .1112306
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .4632441{col 32}{space 2} .0414535{col 43}{space 1}   11.18{col 52}{space 3}0.000{col 60}{space 4} .3818518{col 73}{space 3} .5446364
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .1990325{col 32}{space 2} .0852304{col 43}{space 1}    2.34{col 52}{space 3}0.021{col 60}{space 4} .0309897{col 73}{space 3} .3670752
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 2.336511{col 32}{space 2} .3842065{col 43}{space 1}    6.08{col 52}{space 3}0.000{col 60}{space 4} 1.582015{col 73}{space 3} 3.091007
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHEEur threat2 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       946

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 904.007648
{txt}{col 1}Number of PSUs{col 19}= {res}      946
{txt}{col 49}Average RVI{col 67}= {res}    0.1073
{txt}{col 49}Largest FMI{col 67}= {res}    0.1775
{txt}{col 49}Complete DF{col 67}= {res}       945
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    219.26
{txt}{col 49}        avg{col 67}= {res}    526.37
{txt}{col 49}        max{col 67}= {res}    939.26
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  15{txt},{res}  876.5{txt}){col 67}= {res}     31.76
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}            GHEEur{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat2 {c |}{col 20}{res}{space 2}-.0697346{col 32}{space 2} .0285542{col 43}{space 1}   -2.44{col 52}{space 3}0.015{col 60}{space 4} -.125857{col 73}{space 3}-.0136121
{txt}{space 12}female {c |}{col 20}{res}{space 2} .0047348{col 32}{space 2} .0443769{col 43}{space 1}    0.11{col 52}{space 3}0.915{col 60}{space 4}-.0824726{col 73}{space 3} .0919421
{txt}{space 15}Age {c |}{col 20}{res}{space 2}  .001513{col 32}{space 2} .0021484{col 43}{space 1}    0.70{col 52}{space 3}0.482{col 60}{space 4}-.0027084{col 73}{space 3} .0057344
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0619224{col 32}{space 2} .0145943{col 43}{space 1}   -4.24{col 52}{space 3}0.000{col 60}{space 4}-.0905994{col 73}{space 3}-.0332455
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2} .0221876{col 32}{space 2} .0516209{col 43}{space 1}    0.43{col 52}{space 3}0.668{col 60}{space 4}-.0793746{col 73}{space 3} .1237499
{txt}{space 15}C2  {c |}{col 20}{res}{space 2} .0717915{col 32}{space 2} .0692251{col 43}{space 1}    1.04{col 52}{space 3}0.301{col 60}{space 4}-.0644189{col 73}{space 3} .2080019
{txt}{space 15}DE  {c |}{col 20}{res}{space 2} .1348351{col 32}{space 2} .0663947{col 43}{space 1}    2.03{col 52}{space 3}0.043{col 60}{space 4}  .004256{col 73}{space 3} .2654141
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2}-.1003828{col 32}{space 2} .0679908{col 43}{space 1}   -1.48{col 52}{space 3}0.140{col 60}{space 4} -.233847{col 73}{space 3} .0330813
{txt}full time student  {c |}{col 20}{res}{space 2}-.3172221{col 32}{space 2} .0865272{col 43}{space 1}   -3.67{col 52}{space 3}0.000{col 60}{space 4}-.4870778{col 73}{space 3}-.1473663
{txt}{space 10}retired  {c |}{col 20}{res}{space 2} .0372683{col 32}{space 2} .0696422{col 43}{space 1}    0.54{col 52}{space 3}0.593{col 60}{space 4}-.0996074{col 73}{space 3} .1741441
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2}  .386928{col 32}{space 2} .1823608{col 43}{space 1}    2.12{col 52}{space 3}0.034{col 60}{space 4} .0289704{col 73}{space 3} .7448856
{txt}{space 6}not working  {c |}{col 20}{res}{space 2} .0739809{col 32}{space 2} .0876903{col 43}{space 1}    0.84{col 52}{space 3}0.399{col 60}{space 4}-.0985466{col 73}{space 3} .2465083
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2}-.2888235{col 32}{space 2} .2465909{col 43}{space 1}   -1.17{col 52}{space 3}0.242{col 60}{space 4}-.7727564{col 73}{space 3} .1951094
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .4754267{col 32}{space 2} .0412397{col 43}{space 1}   11.53{col 52}{space 3}0.000{col 60}{space 4} .3944549{col 73}{space 3} .5563986
{txt}{space 11}selfest {c |}{col 20}{res}{space 2}  .299888{col 32}{space 2} .0845423{col 43}{space 1}    3.55{col 52}{space 3}0.000{col 60}{space 4} .1332683{col 73}{space 3} .4665076
{txt}{space 13}_cons {c |}{col 20}{res}{space 2}  2.41283{col 32}{space 2}   .40158{col 43}{space 1}    6.01{col 52}{space 3}0.000{col 60}{space 4} 1.624222{col 73}{space 3} 3.201438
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHEEur threat3 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       969

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 929.292477
{txt}{col 1}Number of PSUs{col 19}= {res}      969
{txt}{col 49}Average RVI{col 67}= {res}    0.0997
{txt}{col 49}Largest FMI{col 67}= {res}    0.1824
{txt}{col 49}Complete DF{col 67}= {res}       968
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    211.99
{txt}{col 49}        avg{col 67}= {res}    543.65
{txt}{col 49}        max{col 67}= {res}    962.25
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  15{txt},{res}  904.4{txt}){col 67}= {res}     31.75
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}            GHEEur{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat3 {c |}{col 20}{res}{space 2}  .047655{col 32}{space 2} .0276422{col 43}{space 1}    1.72{col 52}{space 3}0.085{col 60}{space 4}-.0066341{col 73}{space 3} .1019441
{txt}{space 12}female {c |}{col 20}{res}{space 2}-.0130672{col 32}{space 2} .0435149{col 43}{space 1}   -0.30{col 52}{space 3}0.764{col 60}{space 4}-.0985794{col 73}{space 3}  .072445
{txt}{space 15}Age {c |}{col 20}{res}{space 2} .0021978{col 32}{space 2}  .002137{col 43}{space 1}    1.03{col 52}{space 3}0.304{col 60}{space 4} -.002001{col 73}{space 3} .0063966
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0687288{col 32}{space 2} .0141311{col 43}{space 1}   -4.86{col 52}{space 3}0.000{col 60}{space 4}-.0964885{col 73}{space 3} -.040969
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2}  .023425{col 32}{space 2} .0515143{col 43}{space 1}    0.45{col 52}{space 3}0.650{col 60}{space 4}-.0779141{col 73}{space 3} .1247642
{txt}{space 15}C2  {c |}{col 20}{res}{space 2} .0751202{col 32}{space 2} .0671854{col 43}{space 1}    1.12{col 52}{space 3}0.264{col 60}{space 4}-.0570694{col 73}{space 3} .2073098
{txt}{space 15}DE  {c |}{col 20}{res}{space 2} .1243169{col 32}{space 2} .0648271{col 43}{space 1}    1.92{col 52}{space 3}0.056{col 60}{space 4}-.0031653{col 73}{space 3} .2517992
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2}-.0917434{col 32}{space 2}  .068916{col 43}{space 1}   -1.33{col 52}{space 3}0.183{col 60}{space 4}-.2270184{col 73}{space 3} .0435315
{txt}full time student  {c |}{col 20}{res}{space 2}-.3162444{col 32}{space 2} .0859208{col 43}{space 1}   -3.68{col 52}{space 3}0.000{col 60}{space 4} -.484917{col 73}{space 3}-.1475717
{txt}{space 10}retired  {c |}{col 20}{res}{space 2} .0315944{col 32}{space 2} .0687337{col 43}{space 1}    0.46{col 52}{space 3}0.646{col 60}{space 4}-.1034835{col 73}{space 3} .1666723
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2} .3604532{col 32}{space 2} .1860822{col 43}{space 1}    1.94{col 52}{space 3}0.053{col 60}{space 4}-.0047947{col 73}{space 3} .7257011
{txt}{space 6}not working  {c |}{col 20}{res}{space 2} .0544205{col 32}{space 2} .0862389{col 43}{space 1}    0.63{col 52}{space 3}0.528{col 60}{space 4}-.1152324{col 73}{space 3} .2240734
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2}-.3371868{col 32}{space 2} .2265803{col 43}{space 1}   -1.49{col 52}{space 3}0.137{col 60}{space 4}-.7818352{col 73}{space 3} .1074616
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .4737115{col 32}{space 2} .0408356{col 43}{space 1}   11.60{col 52}{space 3}0.000{col 60}{space 4} .3935377{col 73}{space 3} .5538852
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .2224207{col 32}{space 2} .0826973{col 43}{space 1}    2.69{col 52}{space 3}0.008{col 60}{space 4} .0594063{col 73}{space 3} .3854351
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 2.269197{col 32}{space 2} .3937438{col 43}{space 1}    5.76{col 52}{space 3}0.000{col 60}{space 4} 1.495842{col 73}{space 3} 3.042552
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHEEur threat4 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       962

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 923.500343
{txt}{col 1}Number of PSUs{col 19}= {res}      962
{txt}{col 49}Average RVI{col 67}= {res}    0.1053
{txt}{col 49}Largest FMI{col 67}= {res}    0.1932
{txt}{col 49}Complete DF{col 67}= {res}       961
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    194.17
{txt}{col 49}        avg{col 67}= {res}    551.04
{txt}{col 49}        max{col 67}= {res}    956.05
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  15{txt},{res}  892.5{txt}){col 67}= {res}     43.35
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}            GHEEur{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat4 {c |}{col 20}{res}{space 2}  .206264{col 32}{space 2} .0232302{col 43}{space 1}    8.88{col 52}{space 3}0.000{col 60}{space 4} .1606707{col 73}{space 3} .2518572
{txt}{space 12}female {c |}{col 20}{res}{space 2}  -.02873{col 32}{space 2} .0411992{col 43}{space 1}   -0.70{col 52}{space 3}0.486{col 60}{space 4}-.1096968{col 73}{space 3} .0522368
{txt}{space 15}Age {c |}{col 20}{res}{space 2}-.0003029{col 32}{space 2} .0020504{col 43}{space 1}   -0.15{col 52}{space 3}0.883{col 60}{space 4}-.0043333{col 73}{space 3} .0037274
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0550017{col 32}{space 2} .0138835{col 43}{space 1}   -3.96{col 52}{space 3}0.000{col 60}{space 4}-.0822764{col 73}{space 3}-.0277269
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2}-.0146944{col 32}{space 2} .0502177{col 43}{space 1}   -0.29{col 52}{space 3}0.770{col 60}{space 4}-.1134984{col 73}{space 3} .0841095
{txt}{space 15}C2  {c |}{col 20}{res}{space 2} .0248455{col 32}{space 2} .0656177{col 43}{space 1}    0.38{col 52}{space 3}0.705{col 60}{space 4}-.1042793{col 73}{space 3} .1539703
{txt}{space 15}DE  {c |}{col 20}{res}{space 2} .1056649{col 32}{space 2} .0621861{col 43}{space 1}    1.70{col 52}{space 3}0.090{col 60}{space 4}-.0166251{col 73}{space 3} .2279549
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2}-.0923963{col 32}{space 2} .0673113{col 43}{space 1}   -1.37{col 52}{space 3}0.170{col 60}{space 4}-.2245269{col 73}{space 3} .0397344
{txt}full time student  {c |}{col 20}{res}{space 2}-.2550177{col 32}{space 2} .0845343{col 43}{space 1}   -3.02{col 52}{space 3}0.003{col 60}{space 4}-.4209604{col 73}{space 3}-.0890749
{txt}{space 10}retired  {c |}{col 20}{res}{space 2} .0496826{col 32}{space 2} .0656486{col 43}{space 1}    0.76{col 52}{space 3}0.450{col 60}{space 4}-.0793562{col 73}{space 3} .1787215
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2} .3304255{col 32}{space 2} .1764054{col 43}{space 1}    1.87{col 52}{space 3}0.061{col 60}{space 4}-.0158049{col 73}{space 3} .6766558
{txt}{space 6}not working  {c |}{col 20}{res}{space 2} .0112749{col 32}{space 2} .0814287{col 43}{space 1}    0.14{col 52}{space 3}0.890{col 60}{space 4}-.1490127{col 73}{space 3} .1715625
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2}-.3297954{col 32}{space 2} .1936638{col 43}{space 1}   -1.70{col 52}{space 3}0.089{col 60}{space 4}-.7098506{col 73}{space 3} .0502597
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .3730566{col 32}{space 2} .0426575{col 43}{space 1}    8.75{col 52}{space 3}0.000{col 60}{space 4}  .289304{col 73}{space 3} .4568092
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .1837394{col 32}{space 2} .0788034{col 43}{space 1}    2.33{col 52}{space 3}0.021{col 60}{space 4} .0283189{col 73}{space 3} .3391599
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 1.962979{col 32}{space 2} .3604577{col 43}{space 1}    5.45{col 52}{space 3}0.000{col 60}{space 4} 1.255016{col 73}{space 3} 2.670943
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHEEur threat5 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       959

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res}  917.71578
{txt}{col 1}Number of PSUs{col 19}= {res}      959
{txt}{col 49}Average RVI{col 67}= {res}    0.1018
{txt}{col 49}Largest FMI{col 67}= {res}    0.1691
{txt}{col 49}Complete DF{col 67}= {res}       958
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    236.19
{txt}{col 49}        avg{col 67}= {res}    552.22
{txt}{col 49}        max{col 67}= {res}    952.37
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  15{txt},{res}  893.7{txt}){col 67}= {res}     33.02
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}            GHEEur{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat5 {c |}{col 20}{res}{space 2}-.1141424{col 32}{space 2}  .025351{col 43}{space 1}   -4.50{col 52}{space 3}0.000{col 60}{space 4} -.163913{col 73}{space 3}-.0643717
{txt}{space 12}female {c |}{col 20}{res}{space 2} .0054212{col 32}{space 2} .0433288{col 43}{space 1}    0.13{col 52}{space 3}0.900{col 60}{space 4}-.0797294{col 73}{space 3} .0905718
{txt}{space 15}Age {c |}{col 20}{res}{space 2} .0011484{col 32}{space 2} .0021229{col 43}{space 1}    0.54{col 52}{space 3}0.589{col 60}{space 4}-.0030225{col 73}{space 3} .0053194
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0632886{col 32}{space 2} .0142402{col 43}{space 1}   -4.44{col 52}{space 3}0.000{col 60}{space 4}-.0912692{col 73}{space 3} -.035308
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2} .0226941{col 32}{space 2} .0507443{col 43}{space 1}    0.45{col 52}{space 3}0.655{col 60}{space 4}-.0771719{col 73}{space 3} .1225602
{txt}{space 15}C2  {c |}{col 20}{res}{space 2} .0601275{col 32}{space 2} .0672523{col 43}{space 1}    0.89{col 52}{space 3}0.372{col 60}{space 4}-.0722017{col 73}{space 3} .1924568
{txt}{space 15}DE  {c |}{col 20}{res}{space 2} .1243841{col 32}{space 2} .0641865{col 43}{space 1}    1.94{col 52}{space 3}0.053{col 60}{space 4}-.0018401{col 73}{space 3} .2506083
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2}-.1103463{col 32}{space 2} .0660537{col 43}{space 1}   -1.67{col 52}{space 3}0.095{col 60}{space 4}-.2400065{col 73}{space 3} .0193139
{txt}full time student  {c |}{col 20}{res}{space 2}-.3199995{col 32}{space 2} .0849728{col 43}{space 1}   -3.77{col 52}{space 3}0.000{col 60}{space 4}-.4868004{col 73}{space 3}-.1531986
{txt}{space 10}retired  {c |}{col 20}{res}{space 2} .0345072{col 32}{space 2} .0681341{col 43}{space 1}    0.51{col 52}{space 3}0.613{col 60}{space 4}-.0994073{col 73}{space 3} .1684217
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2} .3708379{col 32}{space 2} .1750113{col 43}{space 1}    2.12{col 52}{space 3}0.034{col 60}{space 4} .0273127{col 73}{space 3} .7143632
{txt}{space 6}not working  {c |}{col 20}{res}{space 2} .0448319{col 32}{space 2} .0900338{col 43}{space 1}    0.50{col 52}{space 3}0.619{col 60}{space 4} -.132249{col 73}{space 3} .2219128
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2}-.3121442{col 32}{space 2} .2194852{col 43}{space 1}   -1.42{col 52}{space 3}0.155{col 60}{space 4}-.7428747{col 73}{space 3} .1185864
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .4453784{col 32}{space 2} .0407548{col 43}{space 1}   10.93{col 52}{space 3}0.000{col 60}{space 4} .3653632{col 73}{space 3} .5253936
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .2697174{col 32}{space 2} .0809272{col 43}{space 1}    3.33{col 52}{space 3}0.001{col 60}{space 4}  .110286{col 73}{space 3} .4291487
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 2.683518{col 32}{space 2} .3880569{col 43}{space 1}    6.92{col 52}{space 3}0.000{col 60}{space 4} 1.921514{col 73}{space 3} 3.445522
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. mi estimate: svy: reg GHwhite threat1 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       981

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 940.170402
{txt}{col 1}Number of PSUs{col 19}= {res}      981
{txt}{col 49}Average RVI{col 67}= {res}    0.1156
{txt}{col 49}Largest FMI{col 67}= {res}    0.3081
{txt}{col 49}Complete DF{col 67}= {res}       980
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}     90.27
{txt}{col 49}        avg{col 67}= {res}    628.56
{txt}{col 49}        max{col 67}= {res}    976.61
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  15{txt},{res}  907.0{txt}){col 67}= {res}      4.67
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           GHwhite{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat1 {c |}{col 20}{res}{space 2} .0872913{col 32}{space 2} .0245071{col 43}{space 1}    3.56{col 52}{space 3}0.000{col 60}{space 4} .0391814{col 73}{space 3} .1354011
{txt}{space 12}female {c |}{col 20}{res}{space 2}-.0488808{col 32}{space 2} .0380252{col 43}{space 1}   -1.29{col 52}{space 3}0.199{col 60}{space 4}-.1235239{col 73}{space 3} .0257623
{txt}{space 15}Age {c |}{col 20}{res}{space 2} -.000932{col 32}{space 2} .0020052{col 43}{space 1}   -0.46{col 52}{space 3}0.642{col 60}{space 4} -.004868{col 73}{space 3}  .003004
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0007161{col 32}{space 2} .0120275{col 43}{space 1}   -0.06{col 52}{space 3}0.953{col 60}{space 4}-.0243674{col 73}{space 3} .0229352
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2} .0468353{col 32}{space 2} .0446918{col 43}{space 1}    1.05{col 52}{space 3}0.295{col 60}{space 4} -.041077{col 73}{space 3} .1347477
{txt}{space 15}C2  {c |}{col 20}{res}{space 2} .0890807{col 32}{space 2}   .05377{col 43}{space 1}    1.66{col 52}{space 3}0.098{col 60}{space 4}-.0166357{col 73}{space 3} .1947971
{txt}{space 15}DE  {c |}{col 20}{res}{space 2} .1151611{col 32}{space 2} .0555821{col 43}{space 1}    2.07{col 52}{space 3}0.039{col 60}{space 4} .0060585{col 73}{space 3} .2242636
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2}-.0539182{col 32}{space 2} .0645021{col 43}{space 1}   -0.84{col 52}{space 3}0.404{col 60}{space 4}-.1806431{col 73}{space 3} .0728067
{txt}full time student  {c |}{col 20}{res}{space 2}-.1905949{col 32}{space 2} .0886828{col 43}{space 1}   -2.15{col 52}{space 3}0.032{col 60}{space 4}-.3646409{col 73}{space 3}-.0165488
{txt}{space 10}retired  {c |}{col 20}{res}{space 2}-.0368166{col 32}{space 2} .0586452{col 43}{space 1}   -0.63{col 52}{space 3}0.530{col 60}{space 4}-.1519183{col 73}{space 3} .0782851
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2}-.2618451{col 32}{space 2} .1992393{col 43}{space 1}   -1.31{col 52}{space 3}0.189{col 60}{space 4}-.6528402{col 73}{space 3}   .12915
{txt}{space 6}not working  {c |}{col 20}{res}{space 2}-.0408122{col 32}{space 2} .0700858{col 43}{space 1}   -0.58{col 52}{space 3}0.561{col 60}{space 4}-.1786508{col 73}{space 3} .0970264
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2} .3429058{col 32}{space 2} .1788715{col 43}{space 1}    1.92{col 52}{space 3}0.056{col 60}{space 4} -.008111{col 73}{space 3} .6939226
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .1412901{col 32}{space 2} .0404383{col 43}{space 1}    3.49{col 52}{space 3}0.001{col 60}{space 4} .0617808{col 73}{space 3} .2207993
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .1381517{col 32}{space 2} .0828626{col 43}{space 1}    1.67{col 52}{space 3}0.099{col 60}{space 4}-.0264627{col 73}{space 3} .3027661
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 1.248721{col 32}{space 2}  .321016{col 43}{space 1}    3.89{col 52}{space 3}0.000{col 60}{space 4} .6185282{col 73}{space 3} 1.878914
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHwhite threat2 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       965

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 921.846826
{txt}{col 1}Number of PSUs{col 19}= {res}      965
{txt}{col 49}Average RVI{col 67}= {res}    0.1186
{txt}{col 49}Largest FMI{col 67}= {res}    0.2840
{txt}{col 49}Complete DF{col 67}= {res}       964
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    103.77
{txt}{col 49}        avg{col 67}= {res}    594.40
{txt}{col 49}        max{col 67}= {res}    960.62
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  15{txt},{res}  890.5{txt}){col 67}= {res}      4.69
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           GHwhite{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat2 {c |}{col 20}{res}{space 2} .0728284{col 32}{space 2} .0238625{col 43}{space 1}    3.05{col 52}{space 3}0.002{col 60}{space 4}  .025934{col 73}{space 3} .1197227
{txt}{space 12}female {c |}{col 20}{res}{space 2}-.0515548{col 32}{space 2} .0379826{col 43}{space 1}   -1.36{col 52}{space 3}0.175{col 60}{space 4} -.126112{col 73}{space 3} .0230025
{txt}{space 15}Age {c |}{col 20}{res}{space 2}-.0006221{col 32}{space 2} .0019286{col 43}{space 1}   -0.32{col 52}{space 3}0.747{col 60}{space 4}-.0044078{col 73}{space 3} .0031637
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2} .0018961{col 32}{space 2} .0119542{col 43}{space 1}    0.16{col 52}{space 3}0.874{col 60}{space 4}-.0216181{col 73}{space 3} .0254102
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2}  .045046{col 32}{space 2} .0450457{col 43}{space 1}    1.00{col 52}{space 3}0.318{col 60}{space 4}-.0435354{col 73}{space 3} .1336273
{txt}{space 15}C2  {c |}{col 20}{res}{space 2} .0867753{col 32}{space 2} .0539058{col 43}{space 1}    1.61{col 52}{space 3}0.108{col 60}{space 4}-.0192008{col 73}{space 3} .1927515
{txt}{space 15}DE  {c |}{col 20}{res}{space 2} .1089459{col 32}{space 2}  .055583{col 43}{space 1}    1.96{col 52}{space 3}0.050{col 60}{space 4} -.000158{col 73}{space 3} .2180498
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2}-.0662418{col 32}{space 2} .0622588{col 43}{space 1}   -1.06{col 52}{space 3}0.288{col 60}{space 4}-.1886004{col 73}{space 3} .0561169
{txt}full time student  {c |}{col 20}{res}{space 2}-.2017703{col 32}{space 2} .0850608{col 43}{space 1}   -2.37{col 52}{space 3}0.018{col 60}{space 4}-.3687134{col 73}{space 3}-.0348272
{txt}{space 10}retired  {c |}{col 20}{res}{space 2}-.0384192{col 32}{space 2} .0585934{col 43}{space 1}   -0.66{col 52}{space 3}0.512{col 60}{space 4}-.1534266{col 73}{space 3} .0765883
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2}-.2364777{col 32}{space 2} .1937122{col 43}{space 1}   -1.22{col 52}{space 3}0.222{col 60}{space 4}-.6166384{col 73}{space 3} .1436829
{txt}{space 6}not working  {c |}{col 20}{res}{space 2}-.0230778{col 32}{space 2} .0718355{col 43}{space 1}   -0.32{col 52}{space 3}0.748{col 60}{space 4} -.164356{col 73}{space 3} .1182004
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2} .4026722{col 32}{space 2} .1928095{col 43}{space 1}    2.09{col 52}{space 3}0.037{col 60}{space 4} .0242957{col 73}{space 3} .7810487
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .1851615{col 32}{space 2}   .04017{col 43}{space 1}    4.61{col 52}{space 3}0.000{col 60}{space 4}   .10611{col 73}{space 3}  .264213
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .1686633{col 32}{space 2}   .08017{col 43}{space 1}    2.10{col 52}{space 3}0.038{col 60}{space 4} .0096792{col 73}{space 3} .3276475
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 1.029723{col 32}{space 2} .3193839{col 43}{space 1}    3.22{col 52}{space 3}0.001{col 60}{space 4} .4026933{col 73}{space 3} 1.656753
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHwhite threat3 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       987

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 945.970404
{txt}{col 1}Number of PSUs{col 19}= {res}      987
{txt}{col 49}Average RVI{col 67}= {res}    0.1119
{txt}{col 49}Largest FMI{col 67}= {res}    0.2845
{txt}{col 49}Complete DF{col 67}= {res}       986
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    103.76
{txt}{col 49}        avg{col 67}= {res}    638.21
{txt}{col 49}        max{col 67}= {res}    982.36
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  15{txt},{res}  916.0{txt}){col 67}= {res}      4.91
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           GHwhite{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat3 {c |}{col 20}{res}{space 2} .0763981{col 32}{space 2} .0223631{col 43}{space 1}    3.42{col 52}{space 3}0.001{col 60}{space 4} .0325087{col 73}{space 3} .1202876
{txt}{space 12}female {c |}{col 20}{res}{space 2}-.0641498{col 32}{space 2} .0385518{col 43}{space 1}   -1.66{col 52}{space 3}0.097{col 60}{space 4}-.1398251{col 73}{space 3} .0115255
{txt}{space 15}Age {c |}{col 20}{res}{space 2}-.0007923{col 32}{space 2} .0019787{col 43}{space 1}   -0.40{col 52}{space 3}0.689{col 60}{space 4}-.0046763{col 73}{space 3} .0030917
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2} .0014122{col 32}{space 2} .0118637{col 43}{space 1}    0.12{col 52}{space 3}0.905{col 60}{space 4}-.0219187{col 73}{space 3} .0247431
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2} .0440298{col 32}{space 2} .0450978{col 43}{space 1}    0.98{col 52}{space 3}0.330{col 60}{space 4}-.0446783{col 73}{space 3} .1327379
{txt}{space 15}C2  {c |}{col 20}{res}{space 2}  .091713{col 32}{space 2} .0533505{col 43}{space 1}    1.72{col 52}{space 3}0.086{col 60}{space 4}-.0131768{col 73}{space 3} .1966028
{txt}{space 15}DE  {c |}{col 20}{res}{space 2} .1156928{col 32}{space 2} .0540195{col 43}{space 1}    2.14{col 52}{space 3}0.033{col 60}{space 4} .0096575{col 73}{space 3} .2217281
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2}-.0642776{col 32}{space 2} .0637787{col 43}{space 1}   -1.01{col 52}{space 3}0.314{col 60}{space 4}-.1895931{col 73}{space 3} .0610378
{txt}full time student  {c |}{col 20}{res}{space 2}-.1797629{col 32}{space 2} .0863441{col 43}{space 1}   -2.08{col 52}{space 3}0.038{col 60}{space 4}-.3492188{col 73}{space 3} -.010307
{txt}{space 10}retired  {c |}{col 20}{res}{space 2}  -.04933{col 32}{space 2} .0584537{col 43}{space 1}   -0.84{col 52}{space 3}0.399{col 60}{space 4}-.1640556{col 73}{space 3} .0653956
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2}-.2589238{col 32}{space 2} .2011882{col 43}{space 1}   -1.29{col 52}{space 3}0.198{col 60}{space 4} -.653742{col 73}{space 3} .1358943
{txt}{space 6}not working  {c |}{col 20}{res}{space 2}-.0461945{col 32}{space 2} .0693276{col 43}{space 1}   -0.67{col 52}{space 3}0.506{col 60}{space 4}-.1825427{col 73}{space 3} .0901537
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2} .3446742{col 32}{space 2} .1757478{col 43}{space 1}    1.96{col 52}{space 3}0.050{col 60}{space 4}-.0002101{col 73}{space 3} .6895586
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .1539434{col 32}{space 2} .0399982{col 43}{space 1}    3.85{col 52}{space 3}0.000{col 60}{space 4} .0752693{col 73}{space 3} .2326175
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .1738928{col 32}{space 2} .0799255{col 43}{space 1}    2.18{col 52}{space 3}0.032{col 60}{space 4} .0153933{col 73}{space 3} .3323922
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 1.156722{col 32}{space 2} .3177944{col 43}{space 1}    3.64{col 52}{space 3}0.000{col 60}{space 4}  .532885{col 73}{space 3}  1.78056
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHwhite threat4 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       981

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 940.223653
{txt}{col 1}Number of PSUs{col 19}= {res}      981
{txt}{col 49}Average RVI{col 67}= {res}    0.1175
{txt}{col 49}Largest FMI{col 67}= {res}    0.3005
{txt}{col 49}Complete DF{col 67}= {res}       980
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}     94.32
{txt}{col 49}        avg{col 67}= {res}    599.99
{txt}{col 49}        max{col 67}= {res}    976.63
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  15{txt},{res}  904.6{txt}){col 67}= {res}      4.30
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           GHwhite{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat4 {c |}{col 20}{res}{space 2} .0438538{col 32}{space 2} .0215701{col 43}{space 1}    2.03{col 52}{space 3}0.042{col 60}{space 4} .0014889{col 73}{space 3} .0862188
{txt}{space 12}female {c |}{col 20}{res}{space 2}-.0517763{col 32}{space 2} .0376663{col 43}{space 1}   -1.37{col 52}{space 3}0.170{col 60}{space 4}-.1257158{col 73}{space 3} .0221632
{txt}{space 15}Age {c |}{col 20}{res}{space 2} -.001645{col 32}{space 2} .0019446{col 43}{space 1}   -0.85{col 52}{space 3}0.398{col 60}{space 4}-.0054624{col 73}{space 3} .0021723
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2} .0030113{col 32}{space 2} .0121385{col 43}{space 1}    0.25{col 52}{space 3}0.804{col 60}{space 4}-.0208792{col 73}{space 3} .0269018
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2} .0334412{col 32}{space 2} .0452319{col 43}{space 1}    0.74{col 52}{space 3}0.460{col 60}{space 4}-.0555357{col 73}{space 3}  .122418
{txt}{space 15}C2  {c |}{col 20}{res}{space 2} .0839056{col 32}{space 2} .0533667{col 43}{space 1}    1.57{col 52}{space 3}0.117{col 60}{space 4}-.0210108{col 73}{space 3}  .188822
{txt}{space 15}DE  {c |}{col 20}{res}{space 2} .1103923{col 32}{space 2} .0539289{col 43}{space 1}    2.05{col 52}{space 3}0.041{col 60}{space 4} .0045319{col 73}{space 3} .2162528
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2}-.0620027{col 32}{space 2}   .06312{col 43}{space 1}   -0.98{col 52}{space 3}0.326{col 60}{space 4}-.1860265{col 73}{space 3}  .062021
{txt}full time student  {c |}{col 20}{res}{space 2}-.2076049{col 32}{space 2} .0891402{col 43}{space 1}   -2.33{col 52}{space 3}0.020{col 60}{space 4}-.3825481{col 73}{space 3}-.0326617
{txt}{space 10}retired  {c |}{col 20}{res}{space 2}-.0422355{col 32}{space 2} .0578119{col 43}{space 1}   -0.73{col 52}{space 3}0.465{col 60}{space 4}-.1557012{col 73}{space 3} .0712301
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2}-.2364149{col 32}{space 2} .1995426{col 43}{space 1}   -1.18{col 52}{space 3}0.236{col 60}{space 4}-.6280067{col 73}{space 3} .1551769
{txt}{space 6}not working  {c |}{col 20}{res}{space 2}-.0586292{col 32}{space 2} .0687067{col 43}{space 1}   -0.85{col 52}{space 3}0.394{col 60}{space 4}-.1937928{col 73}{space 3} .0765344
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2} .3458497{col 32}{space 2} .1902276{col 43}{space 1}    1.82{col 52}{space 3}0.069{col 60}{space 4}-.0274522{col 73}{space 3} .7191515
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2}  .146271{col 32}{space 2} .0405951{col 43}{space 1}    3.60{col 52}{space 3}0.000{col 60}{space 4} .0664413{col 73}{space 3} .2261007
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .1797098{col 32}{space 2} .0814531{col 43}{space 1}    2.21{col 52}{space 3}0.030{col 60}{space 4} .0179899{col 73}{space 3} .3414297
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 1.275132{col 32}{space 2} .3230571{col 43}{space 1}    3.95{col 52}{space 3}0.000{col 60}{space 4} .6408138{col 73}{space 3} 1.909449
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHwhite threat5 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       969

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 927.629667
{txt}{col 1}Number of PSUs{col 19}= {res}      969
{txt}{col 49}Average RVI{col 67}= {res}    0.1182
{txt}{col 49}Largest FMI{col 67}= {res}    0.2765
{txt}{col 49}Complete DF{col 67}= {res}       968
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    108.68
{txt}{col 49}        avg{col 67}= {res}    601.33
{txt}{col 49}        max{col 67}= {res}    964.72
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  15{txt},{res}  894.1{txt}){col 67}= {res}      4.42
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           GHwhite{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat5 {c |}{col 20}{res}{space 2} .0511045{col 32}{space 2} .0220301{col 43}{space 1}    2.32{col 52}{space 3}0.021{col 60}{space 4} .0078338{col 73}{space 3} .0943752
{txt}{space 12}female {c |}{col 20}{res}{space 2}-.0483379{col 32}{space 2} .0377741{col 43}{space 1}   -1.28{col 52}{space 3}0.201{col 60}{space 4}-.1224885{col 73}{space 3} .0258127
{txt}{space 15}Age {c |}{col 20}{res}{space 2}-.0006143{col 32}{space 2} .0019441{col 43}{space 1}   -0.32{col 52}{space 3}0.752{col 60}{space 4}-.0044305{col 73}{space 3}  .003202
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0042677{col 32}{space 2} .0119416{col 43}{space 1}   -0.36{col 52}{space 3}0.721{col 60}{space 4}-.0277613{col 73}{space 3} .0192258
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2} .0493259{col 32}{space 2} .0453607{col 43}{space 1}    1.09{col 52}{space 3}0.278{col 60}{space 4}-.0399021{col 73}{space 3}  .138554
{txt}{space 15}C2  {c |}{col 20}{res}{space 2} .0988937{col 32}{space 2}  .053733{col 43}{space 1}    1.84{col 52}{space 3}0.066{col 60}{space 4}-.0067341{col 73}{space 3} .2045216
{txt}{space 15}DE  {c |}{col 20}{res}{space 2} .1243139{col 32}{space 2} .0554288{col 43}{space 1}    2.24{col 52}{space 3}0.025{col 60}{space 4} .0155125{col 73}{space 3} .2331153
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2}-.0760282{col 32}{space 2} .0627263{col 43}{space 1}   -1.21{col 52}{space 3}0.226{col 60}{space 4}-.1992997{col 73}{space 3} .0472432
{txt}full time student  {c |}{col 20}{res}{space 2}-.1997884{col 32}{space 2} .0869972{col 43}{space 1}   -2.30{col 52}{space 3}0.022{col 60}{space 4}-.3705297{col 73}{space 3}-.0290472
{txt}{space 10}retired  {c |}{col 20}{res}{space 2}  -.04785{col 32}{space 2} .0590202{col 43}{space 1}   -0.81{col 52}{space 3}0.418{col 60}{space 4}-.1636903{col 73}{space 3} .0679902
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2}  -.23783{col 32}{space 2} .1943459{col 43}{space 1}   -1.22{col 52}{space 3}0.221{col 60}{space 4}-.6192323{col 73}{space 3} .1435724
{txt}{space 6}not working  {c |}{col 20}{res}{space 2}-.0407798{col 32}{space 2} .0709803{col 43}{space 1}   -0.57{col 52}{space 3}0.566{col 60}{space 4}-.1803924{col 73}{space 3} .0988328
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2} .3437511{col 32}{space 2} .1826378{col 43}{space 1}    1.88{col 52}{space 3}0.060{col 60}{space 4}-.0146621{col 73}{space 3} .7021642
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .1831688{col 32}{space 2} .0405296{col 43}{space 1}    4.52{col 52}{space 3}0.000{col 60}{space 4} .1033546{col 73}{space 3}  .262983
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .1796297{col 32}{space 2} .0808899{col 43}{space 1}    2.22{col 52}{space 3}0.028{col 60}{space 4} .0193031{col 73}{space 3} .3399563
{txt}{space 13}_cons {c |}{col 20}{res}{space 2}  1.25868{col 32}{space 2} .3182112{col 43}{space 1}    3.96{col 52}{space 3}0.000{col 60}{space 4} .6340407{col 73}{space 3} 1.883319
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. 
. *********************************************************************
. * DISCUSSION IN THE PAPER OF SOME ESTIMATES IN FIGURE 1 IN TERMS OF THE IMPACT 
. * ON HOSTILITY OF ONE STANDARD DEVIATION (SD) INCREASE IN COLLECTIVE AND INDIVIDUAL ECONOMIC THREAT:
. **      NOTE: Only calculated for threat5 (GHEEur) and threat2 (GHEEur) 
. *********************************************************************
. 
. * SD for threat5
. mi estimate: svy: mean threat5
{res}
{txt}Multiple-imputation estimates{col 35}Imputations{col 51}= {res}        10
{txt}Survey: Mean estimation{col 35}Number of obs{col 51}= {res}     1,312

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 35}Population size{col 51}={res} 1,265.2528
{txt}{col 1}Number of PSUs{col 19}= {res}    1,312
{txt}{col 35}Average RVI{col 51}= {res}    0.0000
{txt}{col 35}Largest FMI{col 51}= {res}    0.0000
{txt}{col 35}Complete DF{col 51}= {res}      1311
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 35}DF:     min{col 51}= {res}  1,309.00
{txt}{col 35}        avg{col 51}= {res}  1,309.00
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 35}        max{col 51}= {res}  1,309.00

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 5}threat5 {c |}{col 14}{res}{space 2} 2.701299{col 26}{space 2} .0261361{col 37}{space 5} 2.650026{col 51}{space 3} 2.752572
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}
{res}{txt}
{com}. matrix b = e(b_mi)
{txt}
{com}. scalar m = b[1,1]
{txt}
{com}. gen threat5_v = (threat5 - m)^2 
{txt}(2,032 missing values generated)

{com}. mi estimate: svy: mean threat5_v
{res}
{txt}Multiple-imputation estimates{col 35}Imputations{col 51}= {res}        10
{txt}Survey: Mean estimation{col 35}Number of obs{col 51}= {res}     1,312

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 35}Population size{col 51}={res} 1,265.2528
{txt}{col 1}Number of PSUs{col 19}= {res}    1,312
{txt}{col 35}Average RVI{col 51}= {res}    0.0000
{txt}{col 35}Largest FMI{col 51}= {res}    0.0000
{txt}{col 35}Complete DF{col 51}= {res}      1311
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 35}DF:     min{col 51}= {res}  1,309.00
{txt}{col 35}        avg{col 51}= {res}  1,309.00
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 35}        max{col 51}= {res}  1,309.00

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 3}threat5_v {c |}{col 14}{res}{space 2}  .790976{col 26}{space 2} .0262103{col 37}{space 5} .7395571{col 51}{space 3} .8423949
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}
{res}{txt}
{com}. matrix b = e(b_mi)
{txt}
{com}. scalar threat5_sd2 = b[1,1]
{txt}
{com}. 
. * SD for GHEEur
. mi estimate: svy: mean GHEEur
{res}
{txt}Multiple-imputation estimates{col 35}Imputations{col 51}= {res}        10
{txt}Survey: Mean estimation{col 35}Number of obs{col 51}= {res}     1,130

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 35}Population size{col 51}={res} 1,079.6267
{txt}{col 1}Number of PSUs{col 19}= {res}    1,130
{txt}{col 35}Average RVI{col 51}= {res}    0.0295
{txt}{col 35}Largest FMI{col 51}= {res}    0.0289
{txt}{col 35}Complete DF{col 51}= {res}      1129
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 35}DF:     min{col 51}= {res}    995.51
{txt}{col 35}        avg{col 51}= {res}    995.51
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 35}        max{col 51}= {res}    995.51

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 6}GHEEur {c |}{col 14}{res}{space 2} 2.045792{col 26}{space 2}  .024378{col 37}{space 5} 1.997954{col 51}{space 3}  2.09363
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}
{res}{txt}
{com}. matrix b = e(b_mi)
{txt}
{com}. scalar m = b[1,1]
{txt}
{com}. gen GHEEur_v = (GHEEur - m)^2 
{txt}(4,454 missing values generated)

{com}. mi estimate: svy: mean GHEEur_v
{res}
{txt}Multiple-imputation estimates{col 35}Imputations{col 51}= {res}        10
{txt}Survey: Mean estimation{col 35}Number of obs{col 51}= {res}     1,130

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 35}Population size{col 51}={res} 1,079.6267
{txt}{col 1}Number of PSUs{col 19}= {res}    1,130
{txt}{col 35}Average RVI{col 51}= {res}    0.0642
{txt}{col 35}Largest FMI{col 51}= {res}    0.0612
{txt}{col 35}Complete DF{col 51}= {res}      1129
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 35}DF:     min{col 51}= {res}    741.79
{txt}{col 35}        avg{col 51}= {res}    741.79
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 35}        max{col 51}= {res}    741.79

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 4}GHEEur_v {c |}{col 14}{res}{space 2} .5058815{col 26}{space 2} .0252686{col 37}{space 5} .4562751{col 51}{space 3}  .555488
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}
{res}{txt}
{com}. matrix b = e(b_mi)
{txt}
{com}. scalar GHEEur_sd2 = b[1,1]
{txt}
{com}. 
. * Effect of threat5 on GHEEur
. mi estimate: svy: reg GHEEur threat5 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       959

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res}  917.71578
{txt}{col 1}Number of PSUs{col 19}= {res}      959
{txt}{col 49}Average RVI{col 67}= {res}    0.1018
{txt}{col 49}Largest FMI{col 67}= {res}    0.1691
{txt}{col 49}Complete DF{col 67}= {res}       958
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    236.19
{txt}{col 49}        avg{col 67}= {res}    552.22
{txt}{col 49}        max{col 67}= {res}    952.37
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  15{txt},{res}  893.7{txt}){col 67}= {res}     33.02
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}            GHEEur{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat5 {c |}{col 20}{res}{space 2}-.1141424{col 32}{space 2}  .025351{col 43}{space 1}   -4.50{col 52}{space 3}0.000{col 60}{space 4} -.163913{col 73}{space 3}-.0643717
{txt}{space 12}female {c |}{col 20}{res}{space 2} .0054212{col 32}{space 2} .0433288{col 43}{space 1}    0.13{col 52}{space 3}0.900{col 60}{space 4}-.0797294{col 73}{space 3} .0905718
{txt}{space 15}Age {c |}{col 20}{res}{space 2} .0011484{col 32}{space 2} .0021229{col 43}{space 1}    0.54{col 52}{space 3}0.589{col 60}{space 4}-.0030225{col 73}{space 3} .0053194
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0632886{col 32}{space 2} .0142402{col 43}{space 1}   -4.44{col 52}{space 3}0.000{col 60}{space 4}-.0912692{col 73}{space 3} -.035308
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2} .0226941{col 32}{space 2} .0507443{col 43}{space 1}    0.45{col 52}{space 3}0.655{col 60}{space 4}-.0771719{col 73}{space 3} .1225602
{txt}{space 15}C2  {c |}{col 20}{res}{space 2} .0601275{col 32}{space 2} .0672523{col 43}{space 1}    0.89{col 52}{space 3}0.372{col 60}{space 4}-.0722017{col 73}{space 3} .1924568
{txt}{space 15}DE  {c |}{col 20}{res}{space 2} .1243841{col 32}{space 2} .0641865{col 43}{space 1}    1.94{col 52}{space 3}0.053{col 60}{space 4}-.0018401{col 73}{space 3} .2506083
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2}-.1103463{col 32}{space 2} .0660537{col 43}{space 1}   -1.67{col 52}{space 3}0.095{col 60}{space 4}-.2400065{col 73}{space 3} .0193139
{txt}full time student  {c |}{col 20}{res}{space 2}-.3199995{col 32}{space 2} .0849728{col 43}{space 1}   -3.77{col 52}{space 3}0.000{col 60}{space 4}-.4868004{col 73}{space 3}-.1531986
{txt}{space 10}retired  {c |}{col 20}{res}{space 2} .0345072{col 32}{space 2} .0681341{col 43}{space 1}    0.51{col 52}{space 3}0.613{col 60}{space 4}-.0994073{col 73}{space 3} .1684217
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2} .3708379{col 32}{space 2} .1750113{col 43}{space 1}    2.12{col 52}{space 3}0.034{col 60}{space 4} .0273127{col 73}{space 3} .7143632
{txt}{space 6}not working  {c |}{col 20}{res}{space 2} .0448319{col 32}{space 2} .0900338{col 43}{space 1}    0.50{col 52}{space 3}0.619{col 60}{space 4} -.132249{col 73}{space 3} .2219128
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2}-.3121442{col 32}{space 2} .2194852{col 43}{space 1}   -1.42{col 52}{space 3}0.155{col 60}{space 4}-.7428747{col 73}{space 3} .1185864
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .4453784{col 32}{space 2} .0407548{col 43}{space 1}   10.93{col 52}{space 3}0.000{col 60}{space 4} .3653632{col 73}{space 3} .5253936
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .2697174{col 32}{space 2} .0809272{col 43}{space 1}    3.33{col 52}{space 3}0.001{col 60}{space 4}  .110286{col 73}{space 3} .4291487
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 2.683518{col 32}{space 2} .3880569{col 43}{space 1}    6.92{col 52}{space 3}0.000{col 60}{space 4} 1.921514{col 73}{space 3} 3.445522
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. matrix beta = e(b_mi)
{txt}
{com}. display(sqrt(threat5_sd2)*beta[1,1])/sqrt(GHEEur_sd2)
{res}-.14272635
{txt}
{com}. ** Result: a one SD increase in collective economic threat is predicted to produce a -.14272635 SD decrease in GHEEur
. 
. * SD for threat2
. mi estimate: svy: mean threat2
{res}
{txt}Multiple-imputation estimates{col 35}Imputations{col 51}= {res}        10
{txt}Survey: Mean estimation{col 35}Number of obs{col 51}= {res}     1,272

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 35}Population size{col 51}={res} 1,226.5347
{txt}{col 1}Number of PSUs{col 19}= {res}    1,272
{txt}{col 35}Average RVI{col 51}= {res}    0.0000
{txt}{col 35}Largest FMI{col 51}= {res}    0.0000
{txt}{col 35}Complete DF{col 51}= {res}      1271
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 35}DF:     min{col 51}= {res}  1,269.00
{txt}{col 35}        avg{col 51}= {res}  1,269.00
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 35}        max{col 51}= {res}  1,269.00

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 5}threat2 {c |}{col 14}{res}{space 2} 2.680916{col 26}{space 2} .0260511{col 37}{space 5} 2.629808{col 51}{space 3} 2.732024
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}
{res}{txt}
{com}. matrix b = e(b_mi)
{txt}
{com}. scalar m = b[1,1]
{txt}
{com}. gen threat2_v = (threat2 - m)^2 
{txt}(2,402 missing values generated)

{com}. mi estimate: svy: mean threat2_v
{res}
{txt}Multiple-imputation estimates{col 35}Imputations{col 51}= {res}        10
{txt}Survey: Mean estimation{col 35}Number of obs{col 51}= {res}     1,272

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 35}Population size{col 51}={res} 1,226.5347
{txt}{col 1}Number of PSUs{col 19}= {res}    1,272
{txt}{col 35}Average RVI{col 51}= {res}    0.0000
{txt}{col 35}Largest FMI{col 51}= {res}    0.0000
{txt}{col 35}Complete DF{col 51}= {res}      1271
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 35}DF:     min{col 51}= {res}  1,269.00
{txt}{col 35}        avg{col 51}= {res}  1,269.00
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 35}        max{col 51}= {res}  1,269.00

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}       Mean{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 3}threat2_v {c |}{col 14}{res}{space 2} .7254141{col 26}{space 2} .0261699{col 37}{space 5}  .674073{col 51}{space 3} .7767552
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}
{res}{txt}
{com}. matrix b = e(b_mi)
{txt}
{com}. scalar threat2_sd2 = b[1,1]
{txt}
{com}. 
. * Effect of threat2 on GHEEur
. mi estimate: svy: reg GHEEur threat2 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       946

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 904.007648
{txt}{col 1}Number of PSUs{col 19}= {res}      946
{txt}{col 49}Average RVI{col 67}= {res}    0.1073
{txt}{col 49}Largest FMI{col 67}= {res}    0.1775
{txt}{col 49}Complete DF{col 67}= {res}       945
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    219.26
{txt}{col 49}        avg{col 67}= {res}    526.37
{txt}{col 49}        max{col 67}= {res}    939.26
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  15{txt},{res}  876.5{txt}){col 67}= {res}     31.76
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}            GHEEur{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat2 {c |}{col 20}{res}{space 2}-.0697346{col 32}{space 2} .0285542{col 43}{space 1}   -2.44{col 52}{space 3}0.015{col 60}{space 4} -.125857{col 73}{space 3}-.0136121
{txt}{space 12}female {c |}{col 20}{res}{space 2} .0047348{col 32}{space 2} .0443769{col 43}{space 1}    0.11{col 52}{space 3}0.915{col 60}{space 4}-.0824726{col 73}{space 3} .0919421
{txt}{space 15}Age {c |}{col 20}{res}{space 2}  .001513{col 32}{space 2} .0021484{col 43}{space 1}    0.70{col 52}{space 3}0.482{col 60}{space 4}-.0027084{col 73}{space 3} .0057344
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0619224{col 32}{space 2} .0145943{col 43}{space 1}   -4.24{col 52}{space 3}0.000{col 60}{space 4}-.0905994{col 73}{space 3}-.0332455
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2} .0221876{col 32}{space 2} .0516209{col 43}{space 1}    0.43{col 52}{space 3}0.668{col 60}{space 4}-.0793746{col 73}{space 3} .1237499
{txt}{space 15}C2  {c |}{col 20}{res}{space 2} .0717915{col 32}{space 2} .0692251{col 43}{space 1}    1.04{col 52}{space 3}0.301{col 60}{space 4}-.0644189{col 73}{space 3} .2080019
{txt}{space 15}DE  {c |}{col 20}{res}{space 2} .1348351{col 32}{space 2} .0663947{col 43}{space 1}    2.03{col 52}{space 3}0.043{col 60}{space 4}  .004256{col 73}{space 3} .2654141
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2}-.1003828{col 32}{space 2} .0679908{col 43}{space 1}   -1.48{col 52}{space 3}0.140{col 60}{space 4} -.233847{col 73}{space 3} .0330813
{txt}full time student  {c |}{col 20}{res}{space 2}-.3172221{col 32}{space 2} .0865272{col 43}{space 1}   -3.67{col 52}{space 3}0.000{col 60}{space 4}-.4870778{col 73}{space 3}-.1473663
{txt}{space 10}retired  {c |}{col 20}{res}{space 2} .0372683{col 32}{space 2} .0696422{col 43}{space 1}    0.54{col 52}{space 3}0.593{col 60}{space 4}-.0996074{col 73}{space 3} .1741441
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2}  .386928{col 32}{space 2} .1823608{col 43}{space 1}    2.12{col 52}{space 3}0.034{col 60}{space 4} .0289704{col 73}{space 3} .7448856
{txt}{space 6}not working  {c |}{col 20}{res}{space 2} .0739809{col 32}{space 2} .0876903{col 43}{space 1}    0.84{col 52}{space 3}0.399{col 60}{space 4}-.0985466{col 73}{space 3} .2465083
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2}-.2888235{col 32}{space 2} .2465909{col 43}{space 1}   -1.17{col 52}{space 3}0.242{col 60}{space 4}-.7727564{col 73}{space 3} .1951094
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .4754267{col 32}{space 2} .0412397{col 43}{space 1}   11.53{col 52}{space 3}0.000{col 60}{space 4} .3944549{col 73}{space 3} .5563986
{txt}{space 11}selfest {c |}{col 20}{res}{space 2}  .299888{col 32}{space 2} .0845423{col 43}{space 1}    3.55{col 52}{space 3}0.000{col 60}{space 4} .1332683{col 73}{space 3} .4665076
{txt}{space 13}_cons {c |}{col 20}{res}{space 2}  2.41283{col 32}{space 2}   .40158{col 43}{space 1}    6.01{col 52}{space 3}0.000{col 60}{space 4} 1.624222{col 73}{space 3} 3.201438
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. matrix beta = e(b_mi)
{txt}
{com}. display(sqrt(threat2_sd2)*beta[1,1])/sqrt(GHEEur_sd2)
{res}-.0835058
{txt}
{com}. ** Result: a one SD increase in individual economic threat is predicted to produce a -.0835058 SD decrease in GHEEur
. 
. drop threat5_v- threat2_v
{txt}
{com}. 
. 
. *********************************************************************
. * TABLE A.8B IN THE APPENDIX:
. *       Predictors of Group Hostility under Decoupled Condition, 2016; with Covariates Shown
. * FIGURE A.2 IN THE APPENDIX:
. *       Unstandardized OLS Coefficient Estimates and 95% Confidence Intervals of the Impact of  
. *       Threats on Group Hostility; Threats Entered Simultaneously (2016 estimates)
. **      NOTE: for significance test of difference between 2011 and 2016 estimates, 
. **      see code for FIGURE A.2 below  
. *********************************************************************
. 
. mi estimate: svy: reg GHblack threat1 threat2 threat3 threat4 threat5 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       913

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 873.889165
{txt}{col 1}Number of PSUs{col 19}= {res}      913
{txt}{col 49}Average RVI{col 67}= {res}    0.1203
{txt}{col 49}Largest FMI{col 67}= {res}    0.3025
{txt}{col 49}Complete DF{col 67}= {res}       912
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}     92.32
{txt}{col 49}        avg{col 67}= {res}    507.20
{txt}{col 49}        max{col 67}= {res}    898.29
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  19{txt},{res}  856.2{txt}){col 67}= {res}     25.51
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           GHblack{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat1 {c |}{col 20}{res}{space 2} .0279043{col 32}{space 2} .0289343{col 43}{space 1}    0.96{col 52}{space 3}0.335{col 60}{space 4}-.0289223{col 73}{space 3} .0847309
{txt}{space 11}threat2 {c |}{col 20}{res}{space 2} .0094857{col 32}{space 2} .0317759{col 43}{space 1}    0.30{col 52}{space 3}0.766{col 60}{space 4}-.0531285{col 73}{space 3}    .0721
{txt}{space 11}threat3 {c |}{col 20}{res}{space 2} .0219323{col 32}{space 2} .0297984{col 43}{space 1}    0.74{col 52}{space 3}0.462{col 60}{space 4}-.0366131{col 73}{space 3} .0804776
{txt}{space 11}threat4 {c |}{col 20}{res}{space 2} .1827249{col 32}{space 2} .0252254{col 43}{space 1}    7.24{col 52}{space 3}0.000{col 60}{space 4} .1331178{col 73}{space 3} .2323321
{txt}{space 11}threat5 {c |}{col 20}{res}{space 2}-.0295574{col 32}{space 2} .0308609{col 43}{space 1}   -0.96{col 52}{space 3}0.339{col 60}{space 4}-.0902346{col 73}{space 3} .0311197
{txt}{space 12}female {c |}{col 20}{res}{space 2}-.0962512{col 32}{space 2} .0398075{col 43}{space 1}   -2.42{col 52}{space 3}0.016{col 60}{space 4} -.174424{col 73}{space 3}-.0180783
{txt}{space 15}Age {c |}{col 20}{res}{space 2} .0007933{col 32}{space 2} .0022282{col 43}{space 1}    0.36{col 52}{space 3}0.722{col 60}{space 4}-.0035848{col 73}{space 3} .0051713
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0009163{col 32}{space 2} .0131301{col 43}{space 1}   -0.07{col 52}{space 3}0.944{col 60}{space 4}-.0266949{col 73}{space 3} .0248622
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2}-.0317209{col 32}{space 2}   .05135{col 43}{space 1}   -0.62{col 52}{space 3}0.537{col 60}{space 4} -.132672{col 73}{space 3} .0692302
{txt}{space 15}C2  {c |}{col 20}{res}{space 2}  .055348{col 32}{space 2} .0545747{col 43}{space 1}    1.01{col 52}{space 3}0.311{col 60}{space 4}-.0517978{col 73}{space 3} .1624939
{txt}{space 15}DE  {c |}{col 20}{res}{space 2}-.0036136{col 32}{space 2} .0571286{col 43}{space 1}   -0.06{col 52}{space 3}0.950{col 60}{space 4}-.1159129{col 73}{space 3} .1086857
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2} .0401786{col 32}{space 2} .0726677{col 43}{space 1}    0.55{col 52}{space 3}0.581{col 60}{space 4}-.1027739{col 73}{space 3}  .183131
{txt}full time student  {c |}{col 20}{res}{space 2}-.2475004{col 32}{space 2} .0847183{col 43}{space 1}   -2.92{col 52}{space 3}0.004{col 60}{space 4}-.4137911{col 73}{space 3}-.0812097
{txt}{space 10}retired  {c |}{col 20}{res}{space 2} .0278525{col 32}{space 2} .0691232{col 43}{space 1}    0.40{col 52}{space 3}0.687{col 60}{space 4}-.1079747{col 73}{space 3} .1636796
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2}-.0834979{col 32}{space 2} .1606121{col 43}{space 1}   -0.52{col 52}{space 3}0.603{col 60}{space 4}-.3989236{col 73}{space 3} .2319278
{txt}{space 6}not working  {c |}{col 20}{res}{space 2}-.0076264{col 32}{space 2} .0671746{col 43}{space 1}   -0.11{col 52}{space 3}0.910{col 60}{space 4}     -.14{col 73}{space 3} .1247471
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2}-.0765437{col 32}{space 2} .1784015{col 43}{space 1}   -0.43{col 52}{space 3}0.668{col 60}{space 4} -.426676{col 73}{space 3} .2735886
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .3866452{col 32}{space 2} .0432284{col 43}{space 1}    8.94{col 52}{space 3}0.000{col 60}{space 4}  .301743{col 73}{space 3} .4715475
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .0588576{col 32}{space 2}  .086015{col 43}{space 1}    0.68{col 52}{space 3}0.496{col 60}{space 4}-.1119678{col 73}{space 3}  .229683
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} .7064297{col 32}{space 2} .3820984{col 43}{space 1}    1.85{col 52}{space 3}0.065{col 60}{space 4}-.0437525{col 73}{space 3} 1.456612
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHMus threat1 threat2 threat3 threat4 threat5 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       912

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 874.021016
{txt}{col 1}Number of PSUs{col 19}= {res}      912
{txt}{col 49}Average RVI{col 67}= {res}    0.0966
{txt}{col 49}Largest FMI{col 67}= {res}    0.1537
{txt}{col 49}Complete DF{col 67}= {res}       911
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    265.52
{txt}{col 49}        avg{col 67}= {res}    569.93
{txt}{col 49}        max{col 67}= {res}    848.57
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  19{txt},{res}  873.0{txt}){col 67}= {res}     31.82
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}             GHMus{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat1 {c |}{col 20}{res}{space 2} .0580361{col 32}{space 2} .0311723{col 43}{space 1}    1.86{col 52}{space 3}0.063{col 60}{space 4} -.003208{col 73}{space 3} .1192802
{txt}{space 11}threat2 {c |}{col 20}{res}{space 2}-.0038695{col 32}{space 2} .0320915{col 43}{space 1}   -0.12{col 52}{space 3}0.904{col 60}{space 4}-.0669782{col 73}{space 3} .0592391
{txt}{space 11}threat3 {c |}{col 20}{res}{space 2}-.0138552{col 32}{space 2} .0337392{col 43}{space 1}   -0.41{col 52}{space 3}0.682{col 60}{space 4}-.0801533{col 73}{space 3} .0524429
{txt}{space 11}threat4 {c |}{col 20}{res}{space 2} .2262143{col 32}{space 2} .0276221{col 43}{space 1}    8.19{col 52}{space 3}0.000{col 60}{space 4} .1719449{col 73}{space 3} .2804836
{txt}{space 11}threat5 {c |}{col 20}{res}{space 2}  -.08612{col 32}{space 2} .0320962{col 43}{space 1}   -2.68{col 52}{space 3}0.008{col 60}{space 4}-.1491637{col 73}{space 3}-.0230763
{txt}{space 12}female {c |}{col 20}{res}{space 2}-.1133199{col 32}{space 2} .0443631{col 43}{space 1}   -2.55{col 52}{space 3}0.011{col 60}{space 4}-.2004372{col 73}{space 3}-.0262026
{txt}{space 15}Age {c |}{col 20}{res}{space 2} .0014812{col 32}{space 2} .0021627{col 43}{space 1}    0.68{col 52}{space 3}0.494{col 60}{space 4}-.0027644{col 73}{space 3} .0057268
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2} -.026893{col 32}{space 2} .0143587{col 43}{space 1}   -1.87{col 52}{space 3}0.062{col 60}{space 4}-.0550905{col 73}{space 3} .0013044
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2}-.0124573{col 32}{space 2} .0520968{col 43}{space 1}   -0.24{col 52}{space 3}0.811{col 60}{space 4} -.114784{col 73}{space 3} .0898694
{txt}{space 15}C2  {c |}{col 20}{res}{space 2} .1080695{col 32}{space 2} .0606501{col 43}{space 1}    1.78{col 52}{space 3}0.075{col 60}{space 4}-.0110119{col 73}{space 3} .2271509
{txt}{space 15}DE  {c |}{col 20}{res}{space 2} .0129525{col 32}{space 2} .0695842{col 43}{space 1}    0.19{col 52}{space 3}0.852{col 60}{space 4}-.1238205{col 73}{space 3} .1497256
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2} .0202255{col 32}{space 2} .0732036{col 43}{space 1}    0.28{col 52}{space 3}0.782{col 60}{space 4}-.1234896{col 73}{space 3} .1639406
{txt}full time student  {c |}{col 20}{res}{space 2}-.2352776{col 32}{space 2} .0887926{col 43}{space 1}   -2.65{col 52}{space 3}0.008{col 60}{space 4}-.4095643{col 73}{space 3}-.0609909
{txt}{space 10}retired  {c |}{col 20}{res}{space 2}-.0276537{col 32}{space 2} .0699556{col 43}{space 1}   -0.40{col 52}{space 3}0.693{col 60}{space 4}-.1649885{col 73}{space 3}  .109681
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2} .2790084{col 32}{space 2} .1532118{col 43}{space 1}    1.82{col 52}{space 3}0.069{col 60}{space 4}-.0217879{col 73}{space 3} .5798047
{txt}{space 6}not working  {c |}{col 20}{res}{space 2}  .100154{col 32}{space 2} .0856501{col 43}{space 1}    1.17{col 52}{space 3}0.243{col 60}{space 4}-.0684818{col 73}{space 3} .2687898
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2}-.2674168{col 32}{space 2} .1739495{col 43}{space 1}   -1.54{col 52}{space 3}0.125{col 60}{space 4}-.6088385{col 73}{space 3}  .074005
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2}  .342935{col 32}{space 2} .0497533{col 43}{space 1}    6.89{col 52}{space 3}0.000{col 60}{space 4} .2450203{col 73}{space 3} .4408497
{txt}{space 11}selfest {c |}{col 20}{res}{space 2}  .154298{col 32}{space 2}  .090738{col 43}{space 1}    1.70{col 52}{space 3}0.090{col 60}{space 4}-.0243595{col 73}{space 3} .3329556
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 1.573596{col 32}{space 2} .3998079{col 43}{space 1}    3.94{col 52}{space 3}0.000{col 60}{space 4} .7884847{col 73}{space 3} 2.358708
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHEEur threat1 threat2 threat3 threat4 threat5 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       911

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 874.074143
{txt}{col 1}Number of PSUs{col 19}= {res}      911
{txt}{col 49}Average RVI{col 67}= {res}    0.1049
{txt}{col 49}Largest FMI{col 67}= {res}    0.2132
{txt}{col 49}Complete DF{col 67}= {res}       910
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    164.58
{txt}{col 49}        avg{col 67}= {res}    534.08
{txt}{col 49}        max{col 67}= {res}    905.37
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  19{txt},{res}  861.8{txt}){col 67}= {res}     33.51
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}            GHEEur{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat1 {c |}{col 20}{res}{space 2} .0331326{col 32}{space 2} .0290603{col 43}{space 1}    1.14{col 52}{space 3}0.255{col 60}{space 4}-.0239145{col 73}{space 3} .0901797
{txt}{space 11}threat2 {c |}{col 20}{res}{space 2}-.0057098{col 32}{space 2} .0337664{col 43}{space 1}   -0.17{col 52}{space 3}0.866{col 60}{space 4}-.0720523{col 73}{space 3} .0606327
{txt}{space 11}threat3 {c |}{col 20}{res}{space 2} .0070299{col 32}{space 2} .0321793{col 43}{space 1}    0.22{col 52}{space 3}0.827{col 60}{space 4}-.0561875{col 73}{space 3} .0702472
{txt}{space 11}threat4 {c |}{col 20}{res}{space 2} .1840589{col 32}{space 2} .0248407{col 43}{space 1}    7.41{col 52}{space 3}0.000{col 60}{space 4} .1352995{col 73}{space 3} .2328182
{txt}{space 11}threat5 {c |}{col 20}{res}{space 2}-.0936237{col 32}{space 2} .0317273{col 43}{space 1}   -2.95{col 52}{space 3}0.003{col 60}{space 4}-.1559036{col 73}{space 3}-.0313439
{txt}{space 12}female {c |}{col 20}{res}{space 2}-.0192491{col 32}{space 2} .0429961{col 43}{space 1}   -0.45{col 52}{space 3}0.655{col 60}{space 4}-.1037758{col 73}{space 3} .0652777
{txt}{space 15}Age {c |}{col 20}{res}{space 2}-.0012011{col 32}{space 2} .0021105{col 43}{space 1}   -0.57{col 52}{space 3}0.570{col 60}{space 4}  -.00535{col 73}{space 3} .0029478
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0475558{col 32}{space 2} .0145956{col 43}{space 1}   -3.26{col 52}{space 3}0.001{col 60}{space 4} -.076244{col 73}{space 3}-.0188677
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2}-.0217187{col 32}{space 2} .0501268{col 43}{space 1}   -0.43{col 52}{space 3}0.665{col 60}{space 4}-.1204164{col 73}{space 3}  .076979
{txt}{space 15}C2  {c |}{col 20}{res}{space 2} .0159617{col 32}{space 2} .0670701{col 43}{space 1}    0.24{col 52}{space 3}0.812{col 60}{space 4}-.1160789{col 73}{space 3} .1480024
{txt}{space 15}DE  {c |}{col 20}{res}{space 2}  .099568{col 32}{space 2} .0638839{col 43}{space 1}    1.56{col 52}{space 3}0.120{col 60}{space 4} -.026094{col 73}{space 3}   .22523
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2} -.077464{col 32}{space 2} .0696049{col 43}{space 1}   -1.11{col 52}{space 3}0.266{col 60}{space 4}-.2141066{col 73}{space 3} .0591787
{txt}full time student  {c |}{col 20}{res}{space 2} -.287105{col 32}{space 2} .0830482{col 43}{space 1}   -3.46{col 52}{space 3}0.001{col 60}{space 4}-.4501766{col 73}{space 3}-.1240334
{txt}{space 10}retired  {c |}{col 20}{res}{space 2} .0667484{col 32}{space 2} .0675539{col 43}{space 1}    0.99{col 52}{space 3}0.324{col 60}{space 4}-.0660734{col 73}{space 3} .1995703
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2} .3248102{col 32}{space 2} .1673273{col 43}{space 1}    1.94{col 52}{space 3}0.053{col 60}{space 4}-.0036353{col 73}{space 3} .6532558
{txt}{space 6}not working  {c |}{col 20}{res}{space 2} .0211777{col 32}{space 2} .0833068{col 43}{space 1}    0.25{col 52}{space 3}0.800{col 60}{space 4} -.142812{col 73}{space 3} .1851674
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2}-.2840251{col 32}{space 2} .2159007{col 43}{space 1}   -1.32{col 52}{space 3}0.189{col 60}{space 4}-.7077492{col 73}{space 3} .1396989
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .3516635{col 32}{space 2} .0447095{col 43}{space 1}    7.87{col 52}{space 3}0.000{col 60}{space 4} .2638712{col 73}{space 3} .4394558
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .1863092{col 32}{space 2} .0829145{col 43}{space 1}    2.25{col 52}{space 3}0.026{col 60}{space 4}  .022596{col 73}{space 3} .3500225
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 2.104128{col 32}{space 2} .3945139{col 43}{space 1}    5.33{col 52}{space 3}0.000{col 60}{space 4} 1.329286{col 73}{space 3} 2.878969
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHwhite threat1 threat2 threat3 threat4 threat5 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       918

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 880.746933
{txt}{col 1}Number of PSUs{col 19}= {res}      918
{txt}{col 49}Average RVI{col 67}= {res}    0.1183
{txt}{col 49}Largest FMI{col 67}= {res}    0.3252
{txt}{col 49}Complete DF{col 67}= {res}       917
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}     81.39
{txt}{col 49}        avg{col 67}= {res}    568.65
{txt}{col 49}        max{col 67}= {res}    913.89
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  19{txt},{res}  863.2{txt}){col 67}= {res}      4.01
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           GHwhite{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}threat1 {c |}{col 20}{res}{space 2} .0606374{col 32}{space 2} .0276963{col 43}{space 1}    2.19{col 52}{space 3}0.029{col 60}{space 4} .0062549{col 73}{space 3}   .11502
{txt}{space 11}threat2 {c |}{col 20}{res}{space 2} .0586692{col 32}{space 2} .0292668{col 43}{space 1}    2.00{col 52}{space 3}0.046{col 60}{space 4} .0011006{col 73}{space 3} .1162378
{txt}{space 11}threat3 {c |}{col 20}{res}{space 2} .0158332{col 32}{space 2} .0270404{col 43}{space 1}    0.59{col 52}{space 3}0.558{col 60}{space 4}-.0372572{col 73}{space 3} .0689237
{txt}{space 11}threat4 {c |}{col 20}{res}{space 2} .0230823{col 32}{space 2} .0237759{col 43}{space 1}    0.97{col 52}{space 3}0.332{col 60}{space 4} -.023603{col 73}{space 3} .0697676
{txt}{space 11}threat5 {c |}{col 20}{res}{space 2}-.0038212{col 32}{space 2} .0287071{col 43}{space 1}   -0.13{col 52}{space 3}0.894{col 60}{space 4}-.0602358{col 73}{space 3} .0525934
{txt}{space 12}female {c |}{col 20}{res}{space 2}-.0441005{col 32}{space 2} .0389759{col 43}{space 1}   -1.13{col 52}{space 3}0.258{col 60}{space 4}-.1206147{col 73}{space 3} .0324138
{txt}{space 15}Age {c |}{col 20}{res}{space 2}-.0016075{col 32}{space 2} .0020043{col 43}{space 1}   -0.80{col 52}{space 3}0.423{col 60}{space 4}-.0055424{col 73}{space 3} .0023274
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2} .0024381{col 32}{space 2} .0125668{col 43}{space 1}    0.19{col 52}{space 3}0.846{col 60}{space 4}-.0223078{col 73}{space 3}  .027184
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2} .0259814{col 32}{space 2} .0455604{col 43}{space 1}    0.57{col 52}{space 3}0.569{col 60}{space 4}-.0636422{col 73}{space 3}  .115605
{txt}{space 15}C2  {c |}{col 20}{res}{space 2} .0799885{col 32}{space 2} .0544064{col 43}{space 1}    1.47{col 52}{space 3}0.142{col 60}{space 4}-.0269843{col 73}{space 3} .1869612
{txt}{space 15}DE  {c |}{col 20}{res}{space 2} .0926792{col 32}{space 2}  .056336{col 43}{space 1}    1.65{col 52}{space 3}0.100{col 60}{space 4}-.0179109{col 73}{space 3} .2032692
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2}-.0481003{col 32}{space 2} .0668648{col 43}{space 1}   -0.72{col 52}{space 3}0.472{col 60}{space 4}-.1794942{col 73}{space 3} .0832936
{txt}full time student  {c |}{col 20}{res}{space 2}-.1753618{col 32}{space 2} .0888119{col 43}{space 1}   -1.97{col 52}{space 3}0.049{col 60}{space 4}-.3496795{col 73}{space 3}-.0010442
{txt}{space 10}retired  {c |}{col 20}{res}{space 2}-.0309912{col 32}{space 2} .0596634{col 43}{space 1}   -0.52{col 52}{space 3}0.604{col 60}{space 4}-.1481077{col 73}{space 3} .0861253
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2}-.2654428{col 32}{space 2} .1922848{col 43}{space 1}   -1.38{col 52}{space 3}0.168{col 60}{space 4}-.6428269{col 73}{space 3} .1119414
{txt}{space 6}not working  {c |}{col 20}{res}{space 2}-.0483128{col 32}{space 2} .0720635{col 43}{space 1}   -0.67{col 52}{space 3}0.503{col 60}{space 4}-.1901067{col 73}{space 3}  .093481
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2} .3910435{col 32}{space 2} .1894203{col 43}{space 1}    2.06{col 52}{space 3}0.039{col 60}{space 4} .0192942{col 73}{space 3} .7627929
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .1647738{col 32}{space 2} .0430644{col 43}{space 1}    3.83{col 52}{space 3}0.000{col 60}{space 4} .0800621{col 73}{space 3} .2494855
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .1063963{col 32}{space 2} .0841154{col 43}{space 1}    1.26{col 52}{space 3}0.210{col 60}{space 4}-.0609547{col 73}{space 3} .2737472
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} .9494713{col 32}{space 2} .3407311{col 43}{space 1}    2.79{col 52}{space 3}0.005{col 60}{space 4} .2804636{col 73}{space 3} 1.618479
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. 
. *********************************************************************
. * TABLE A.9B IN THE APPENDIX:
. *       Predictors of Group Hostility under Decoupled Condition, 2016; with Hostility Toward White British
. * FIGURE 2 IN THE PAPER (2016 estimates):
. *       Unstandardized OLS Coefficient Estimates and 95% Confidence Intervals of the Impact of Threats
. *       on Group Hostility; Threats Entered Simultaneaously and with Hostility Toward White British
. **      NOTE: for significance test of difference between 2011 and 2016 estimates, 
. **      see code for FIGURE 2 below 
. *********************************************************************
. 
. mi estimate: svy: reg GHblack GHwhite threat1 threat2 threat3 threat4 threat5 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       904

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 867.233244
{txt}{col 1}Number of PSUs{col 19}= {res}      904
{txt}{col 49}Average RVI{col 67}= {res}    0.1329
{txt}{col 49}Largest FMI{col 67}= {res}    0.2645
{txt}{col 49}Complete DF{col 67}= {res}       903
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    115.85
{txt}{col 49}        avg{col 67}= {res}    469.97
{txt}{col 49}        max{col 67}= {res}    893.48
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  20{txt},{res}  839.6{txt}){col 67}= {res}     39.92
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           GHblack{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}GHwhite {c |}{col 20}{res}{space 2} .3483211{col 32}{space 2} .0455628{col 43}{space 1}    7.64{col 52}{space 3}0.000{col 60}{space 4} .2585301{col 73}{space 3} .4381122
{txt}{space 11}threat1 {c |}{col 20}{res}{space 2} .0094313{col 32}{space 2} .0271298{col 43}{space 1}    0.35{col 52}{space 3}0.728{col 60}{space 4}-.0438549{col 73}{space 3} .0627175
{txt}{space 11}threat2 {c |}{col 20}{res}{space 2}-.0073306{col 32}{space 2} .0303376{col 43}{space 1}   -0.24{col 52}{space 3}0.809{col 60}{space 4}-.0670976{col 73}{space 3} .0524363
{txt}{space 11}threat3 {c |}{col 20}{res}{space 2} .0134799{col 32}{space 2} .0292336{col 43}{space 1}    0.46{col 52}{space 3}0.645{col 60}{space 4}-.0439349{col 73}{space 3} .0708948
{txt}{space 11}threat4 {c |}{col 20}{res}{space 2} .1733378{col 32}{space 2} .0237411{col 43}{space 1}    7.30{col 52}{space 3}0.000{col 60}{space 4}  .126667{col 73}{space 3} .2200087
{txt}{space 11}threat5 {c |}{col 20}{res}{space 2}-.0291809{col 32}{space 2} .0288678{col 43}{space 1}   -1.01{col 52}{space 3}0.313{col 60}{space 4}-.0859999{col 73}{space 3}  .027638
{txt}{space 12}female {c |}{col 20}{res}{space 2}-.0748607{col 32}{space 2} .0369582{col 43}{space 1}   -2.03{col 52}{space 3}0.043{col 60}{space 4} -.147446{col 73}{space 3}-.0022754
{txt}{space 15}Age {c |}{col 20}{res}{space 2} .0014082{col 32}{space 2} .0020688{col 43}{space 1}    0.68{col 52}{space 3}0.496{col 60}{space 4}-.0026557{col 73}{space 3} .0054721
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0026496{col 32}{space 2} .0122928{col 43}{space 1}   -0.22{col 52}{space 3}0.829{col 60}{space 4}-.0267976{col 73}{space 3} .0214984
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2}-.0391904{col 32}{space 2} .0487576{col 43}{space 1}   -0.80{col 52}{space 3}0.422{col 60}{space 4}-.1349738{col 73}{space 3}  .056593
{txt}{space 15}C2  {c |}{col 20}{res}{space 2} .0273929{col 32}{space 2} .0540502{col 43}{space 1}    0.51{col 52}{space 3}0.612{col 60}{space 4}-.0787794{col 73}{space 3} .1335653
{txt}{space 15}DE  {c |}{col 20}{res}{space 2}-.0367743{col 32}{space 2} .0540373{col 43}{space 1}   -0.68{col 52}{space 3}0.497{col 60}{space 4}-.1429781{col 73}{space 3} .0694295
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2} .0545237{col 32}{space 2} .0665884{col 43}{space 1}    0.82{col 52}{space 3}0.414{col 60}{space 4}-.0766095{col 73}{space 3} .1856569
{txt}full time student  {c |}{col 20}{res}{space 2}-.1782464{col 32}{space 2} .0755435{col 43}{space 1}   -2.36{col 52}{space 3}0.019{col 60}{space 4}-.3265302{col 73}{space 3}-.0299626
{txt}{space 10}retired  {c |}{col 20}{res}{space 2} .0354256{col 32}{space 2}  .065352{col 43}{space 1}    0.54{col 52}{space 3}0.588{col 60}{space 4}-.0929778{col 73}{space 3} .1638289
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2} .0080738{col 32}{space 2} .1294845{col 43}{space 1}    0.06{col 52}{space 3}0.950{col 60}{space 4}-.2462733{col 73}{space 3} .2624209
{txt}{space 6}not working  {c |}{col 20}{res}{space 2} .0131594{col 32}{space 2} .0650309{col 43}{space 1}    0.20{col 52}{space 3}0.840{col 60}{space 4}-.1153457{col 73}{space 3} .1416645
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2}-.2148434{col 32}{space 2} .2173409{col 43}{space 1}   -0.99{col 52}{space 3}0.323{col 60}{space 4}-.6414015{col 73}{space 3} .2117147
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .3330903{col 32}{space 2} .0432147{col 43}{space 1}    7.71{col 52}{space 3}0.000{col 60}{space 4} .2482049{col 73}{space 3} .4179756
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .0167292{col 32}{space 2} .0805306{col 43}{space 1}    0.21{col 52}{space 3}0.836{col 60}{space 4} -.142774{col 73}{space 3} .1762324
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} .3810285{col 32}{space 2} .3833242{col 43}{space 1}    0.99{col 52}{space 3}0.321{col 60}{space 4}-.3718817{col 73}{space 3} 1.133939
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHMus GHwhite threat1 threat2 threat3 threat4 threat5 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       904

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 867.981367
{txt}{col 1}Number of PSUs{col 19}= {res}      904
{txt}{col 49}Average RVI{col 67}= {res}    0.0998
{txt}{col 49}Largest FMI{col 67}= {res}    0.1577
{txt}{col 49}Complete DF{col 67}= {res}       903
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    255.62
{txt}{col 49}        avg{col 67}= {res}    564.30
{txt}{col 49}        max{col 67}= {res}    860.75
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  20{txt},{res}  865.2{txt}){col 67}= {res}     42.39
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}             GHMus{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}GHwhite {c |}{col 20}{res}{space 2} .2546442{col 32}{space 2}  .048855{col 43}{space 1}    5.21{col 52}{space 3}0.000{col 60}{space 4} .1587019{col 73}{space 3} .3505865
{txt}{space 11}threat1 {c |}{col 20}{res}{space 2} .0434108{col 32}{space 2} .0310232{col 43}{space 1}    1.40{col 52}{space 3}0.162{col 60}{space 4}-.0175244{col 73}{space 3} .1043461
{txt}{space 11}threat2 {c |}{col 20}{res}{space 2}-.0165672{col 32}{space 2}  .032668{col 43}{space 1}   -0.51{col 52}{space 3}0.612{col 60}{space 4}-.0808702{col 73}{space 3} .0477359
{txt}{space 11}threat3 {c |}{col 20}{res}{space 2}-.0210769{col 32}{space 2} .0337497{col 43}{space 1}   -0.62{col 52}{space 3}0.533{col 60}{space 4}-.0873845{col 73}{space 3} .0452308
{txt}{space 11}threat4 {c |}{col 20}{res}{space 2} .2187632{col 32}{space 2} .0270418{col 43}{space 1}    8.09{col 52}{space 3}0.000{col 60}{space 4} .1656388{col 73}{space 3} .2718876
{txt}{space 11}threat5 {c |}{col 20}{res}{space 2}-.0850948{col 32}{space 2} .0319274{col 43}{space 1}   -2.67{col 52}{space 3}0.008{col 60}{space 4}-.1478172{col 73}{space 3}-.0223725
{txt}{space 12}female {c |}{col 20}{res}{space 2} -.096632{col 32}{space 2} .0429964{col 43}{space 1}   -2.25{col 52}{space 3}0.025{col 60}{space 4}-.1810637{col 73}{space 3}-.0122003
{txt}{space 15}Age {c |}{col 20}{res}{space 2} .0019446{col 32}{space 2} .0021039{col 43}{space 1}    0.92{col 52}{space 3}0.356{col 60}{space 4}-.0021853{col 73}{space 3} .0060744
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0275148{col 32}{space 2} .0136243{col 43}{space 1}   -2.02{col 52}{space 3}0.044{col 60}{space 4}-.0542685{col 73}{space 3}-.0007611
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2}-.0172148{col 32}{space 2} .0508545{col 43}{space 1}   -0.34{col 52}{space 3}0.735{col 60}{space 4}-.1170749{col 73}{space 3} .0826454
{txt}{space 15}C2  {c |}{col 20}{res}{space 2} .0885397{col 32}{space 2} .0609071{col 43}{space 1}    1.45{col 52}{space 3}0.147{col 60}{space 4}-.0311209{col 73}{space 3} .2082002
{txt}{space 15}DE  {c |}{col 20}{res}{space 2}-.0074276{col 32}{space 2} .0674453{col 43}{space 1}   -0.11{col 52}{space 3}0.912{col 60}{space 4}-.1400339{col 73}{space 3} .1251786
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2} .0313002{col 32}{space 2} .0683849{col 43}{space 1}    0.46{col 52}{space 3}0.647{col 60}{space 4}-.1030073{col 73}{space 3} .1656078
{txt}full time student  {c |}{col 20}{res}{space 2}-.1902986{col 32}{space 2} .0846946{col 43}{space 1}   -2.25{col 52}{space 3}0.025{col 60}{space 4}-.3565399{col 73}{space 3}-.0240572
{txt}{space 10}retired  {c |}{col 20}{res}{space 2}-.0262848{col 32}{space 2} .0693093{col 43}{space 1}   -0.38{col 52}{space 3}0.705{col 60}{space 4}-.1623421{col 73}{space 3} .1097726
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2} .3458027{col 32}{space 2} .1554585{col 43}{space 1}    2.22{col 52}{space 3}0.026{col 60}{space 4} .0406045{col 73}{space 3} .6510009
{txt}{space 6}not working  {c |}{col 20}{res}{space 2} .1162256{col 32}{space 2} .0841592{col 43}{space 1}    1.38{col 52}{space 3}0.168{col 60}{space 4}-.0495081{col 73}{space 3} .2819594
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2}-.3686132{col 32}{space 2} .2004981{col 43}{space 1}   -1.84{col 52}{space 3}0.066{col 60}{space 4}-.7621357{col 73}{space 3} .0249093
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .3075376{col 32}{space 2} .0493492{col 43}{space 1}    6.23{col 52}{space 3}0.000{col 60}{space 4} .2104626{col 73}{space 3} .4046125
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .1220368{col 32}{space 2} .0896322{col 43}{space 1}    1.36{col 52}{space 3}0.174{col 60}{space 4}-.0543607{col 73}{space 3} .2984342
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 1.321716{col 32}{space 2} .3998766{col 43}{space 1}    3.31{col 52}{space 3}0.001{col 60}{space 4} .5363016{col 73}{space 3}  2.10713
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHEEur GHwhite threat1 threat2 threat3 threat4 threat5 female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       905

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 869.441149
{txt}{col 1}Number of PSUs{col 19}= {res}      905
{txt}{col 49}Average RVI{col 67}= {res}    0.1097
{txt}{col 49}Largest FMI{col 67}= {res}    0.2213
{txt}{col 49}Complete DF{col 67}= {res}       904
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    154.98
{txt}{col 49}        avg{col 67}= {res}    513.58
{txt}{col 49}        max{col 67}= {res}    898.93
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  20{txt},{res}  855.5{txt}){col 67}= {res}     37.98
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}            GHEEur{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}GHwhite {c |}{col 20}{res}{space 2} .1790312{col 32}{space 2} .0491621{col 43}{space 1}    3.64{col 52}{space 3}0.000{col 60}{space 4}  .082404{col 73}{space 3} .2756584
{txt}{space 11}threat1 {c |}{col 20}{res}{space 2} .0242707{col 32}{space 2} .0290284{col 43}{space 1}    0.84{col 52}{space 3}0.403{col 60}{space 4}-.0327144{col 73}{space 3} .0812559
{txt}{space 11}threat2 {c |}{col 20}{res}{space 2}-.0147153{col 32}{space 2} .0339375{col 43}{space 1}   -0.43{col 52}{space 3}0.665{col 60}{space 4}-.0813975{col 73}{space 3}  .051967
{txt}{space 11}threat3 {c |}{col 20}{res}{space 2} .0018616{col 32}{space 2} .0325065{col 43}{space 1}    0.06{col 52}{space 3}0.954{col 60}{space 4}-.0619839{col 73}{space 3} .0657071
{txt}{space 11}threat4 {c |}{col 20}{res}{space 2} .1815412{col 32}{space 2} .0244506{col 43}{space 1}    7.42{col 52}{space 3}0.000{col 60}{space 4} .1335464{col 73}{space 3} .2295359
{txt}{space 11}threat5 {c |}{col 20}{res}{space 2}-.0946823{col 32}{space 2} .0313185{col 43}{space 1}   -3.02{col 52}{space 3}0.003{col 60}{space 4}-.1561628{col 73}{space 3}-.0332017
{txt}{space 12}female {c |}{col 20}{res}{space 2}-.0096918{col 32}{space 2} .0425653{col 43}{space 1}   -0.23{col 52}{space 3}0.820{col 60}{space 4}-.0933652{col 73}{space 3} .0739815
{txt}{space 15}Age {c |}{col 20}{res}{space 2}-.0008573{col 32}{space 2}  .002068{col 43}{space 1}   -0.41{col 52}{space 3}0.679{col 60}{space 4}-.0049235{col 73}{space 3} .0032089
{txt}{space 11}edu_age {c |}{col 20}{res}{space 2}-.0468613{col 32}{space 2}  .014137{col 43}{space 1}   -3.31{col 52}{space 3}0.001{col 60}{space 4} -.074642{col 73}{space 3}-.0190806
{txt}{space 18} {c |}
{space 7}SocialGrade {c |}
{space 15}C1  {c |}{col 20}{res}{space 2}-.0243258{col 32}{space 2} .0502461{col 43}{space 1}   -0.48{col 52}{space 3}0.629{col 60}{space 4}-.1232892{col 73}{space 3} .0746375
{txt}{space 15}C2  {c |}{col 20}{res}{space 2} .0037674{col 32}{space 2} .0664245{col 43}{space 1}    0.06{col 52}{space 3}0.955{col 60}{space 4}-.1270491{col 73}{space 3}  .134584
{txt}{space 15}DE  {c |}{col 20}{res}{space 2} .0850724{col 32}{space 2} .0636668{col 43}{space 1}    1.34{col 52}{space 3}0.182{col 60}{space 4}-.0401674{col 73}{space 3} .2103123
{txt}{space 18} {c |}
{space 7}work_status {c |}
working part time  {c |}{col 20}{res}{space 2}-.0693545{col 32}{space 2} .0660116{col 43}{space 1}   -1.05{col 52}{space 3}0.294{col 60}{space 4}-.1989833{col 73}{space 3} .0602742
{txt}full time student  {c |}{col 20}{res}{space 2}-.2546757{col 32}{space 2} .0786456{col 43}{space 1}   -3.24{col 52}{space 3}0.001{col 60}{space 4}-.4091125{col 73}{space 3}-.1002388
{txt}{space 10}retired  {c |}{col 20}{res}{space 2} .0715281{col 32}{space 2} .0670034{col 43}{space 1}    1.07{col 52}{space 3}0.286{col 60}{space 4}-.0602031{col 73}{space 3} .2032593
{txt}{space 7}unemployed  {c |}{col 20}{res}{space 2} .3728234{col 32}{space 2} .1837034{col 43}{space 1}    2.03{col 52}{space 3}0.043{col 60}{space 4} .0122439{col 73}{space 3} .7334029
{txt}{space 6}not working  {c |}{col 20}{res}{space 2} .0296039{col 32}{space 2} .0818799{col 43}{space 1}    0.36{col 52}{space 3}0.718{col 60}{space 4}-.1315939{col 73}{space 3} .1908016
{txt}{space 18} {c |}
{space 12}UKborn {c |}{col 20}{res}{space 2}-.3543532{col 32}{space 2} .2367902{col 43}{space 1}   -1.50{col 52}{space 3}0.135{col 60}{space 4}-.8190793{col 73}{space 3} .1103728
{txt}{space 8}authvalues {c |}{col 20}{res}{space 2} .3236423{col 32}{space 2} .0455925{col 43}{space 1}    7.10{col 52}{space 3}0.000{col 60}{space 4} .2340678{col 73}{space 3} .4132168
{txt}{space 11}selfest {c |}{col 20}{res}{space 2} .1639882{col 32}{space 2} .0846316{col 43}{space 1}    1.94{col 52}{space 3}0.054{col 60}{space 4}-.0031923{col 73}{space 3} .3311686
{txt}{space 13}_cons {c |}{col 20}{res}{space 2}   1.9055{col 32}{space 2} .4036957{col 43}{space 1}    4.72{col 52}{space 3}0.000{col 60}{space 4} 1.112564{col 73}{space 3} 2.698436
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. 
. *****************************************************************************************************************
. *   Combining and Comparing 2011 and 2016       
. *****************************************************************************************************************
. 
. use "W1 imputed.dta", clear
{txt}
{com}. 
. save "W1 W4 imputed.dta", replace
{txt}(note: file W1 W4 imputed.dta not found)
file W1 W4 imputed.dta saved

{com}. 
. keep GHblack GHMus GHEEur GHwhite threat1 threat2 threat3 threat4 threat5 female Age edu_age SocialGrade work_status UKborn authvalues selfest treatment _mi_m _mi_id _mi_miss wave W8
{txt}
{com}. drop if treatment == 1
{txt}(3,552 observations deleted)

{com}. 
. save "W1 W4 imputed.dta", replace
{txt}file W1 W4 imputed.dta saved

{com}. 
. use "W4 imputed.dta", clear
{txt}( )

{com}. 
. save "W4 imputed temp.dta", replace
{txt}(note: file W4 imputed temp.dta not found)
file W4 imputed temp.dta saved

{com}. 
. keep GHblack GHMus GHEEur GHwhite threat1 threat2 threat3 threat4 threat5 female Age edu_age SocialGrade work_status UKborn authvalues selfest _mi_m _mi_id _mi_miss wave W8
{txt}
{com}. 
. save "W4 imputed temp.dta", replace
{txt}file W4 imputed temp.dta saved

{com}. 
. use "W1 W4 imputed.dta", clear
{txt}
{com}. 
. append using "W4 imputed temp.dta"
{txt}(label UKborn already defined)
(label SocialGrade already defined)
(label female already defined)
(label wave already defined)

{com}. 
. 
. *********************************************************************
. * FIGURE 1 IN THE PAPER:                      
. *       Unstandardized OLS Coefficient Estimates and 95% Confidence Intervals of the Impact of Threats on Group Hostility; 
. *       Threats Entered Individually
. *       (comparing 2011 to 2016) 
. *********************************************************************
. 
. * NOTE: the following models are estimated to check whether the 2011 and 2016 effects are different at .05 level
. ** this is indicated by the p-value associated with the c.threat[]##wave interaction effect
. 
. mi estimate: svy: reg GHblack c.threat1##wave female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest 
{txt}{p}
(system variable _mi_id updated due to changed number of obs.)
{p_end}
{p}
(imputed variables
{res}auth1 auth2 auth3 est1 est2 est3 est4 est5 GHbb1 GHbb2 GHbb3 GHbb4 GHbb5 GHbb6 GHbb7 GHbb8 GHmu1 GHmu2 GHmu3 GHmu4 GHmu5 GHmu6 GHmu7 GHmu8 GHee1 GHee2 GHee3 GHee4 GHee5 GHee6 GHee7 GHee8 GHwb1 GHwb2 GHwb3 GHwb4 GHwb5 GHwb6 GHwb7 GHwb8 SDbb1 SDbb2 SDbb3 SDmu1 SDmu2 SDmu3 SDee1 SDee2 SDee3
{txt}unregistered because not in {it:m}=0)
{p_end}
{p}
(1556 {it:m}=0 obs. now marked as complete)
{p_end}
(15560 {it:m}>0 marginal obs. dropped)
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       852

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 814.904318
{txt}{col 1}Number of PSUs{col 19}= {res}      852
{txt}{col 49}Average RVI{col 67}= {res}    0.0000
{txt}{col 49}Largest FMI{col 67}= {res}    0.0000
{txt}{col 49}Complete DF{col 67}= {res}       851
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    849.01
{txt}{col 49}        avg{col 67}= {res}    849.01
{txt}{col 49}        max{col 67}= {res}    849.01
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  17{txt},{res}  849.0{txt}){col 67}= {res}     19.37
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}              GHblack{col 23}{c |}      Coef.{col 35}   Std. Err.{col 47}      t{col 55}   P>|t|{col 63}     [95% Con{col 76}f. Interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 14}threat1 {c |}{col 23}{res}{space 2} .1112002{col 35}{space 2} .0482216{col 46}{space 1}    2.31{col 55}{space 3}0.021{col 63}{space 4} .0165525{col 76}{space 3} .2058478
{txt}{space 21} {c |}
{space 17}wave {c |}
survey wave 4 (2016)  {c |}{col 23}{res}{space 2} .0747355{col 35}{space 2} .1382434{col 46}{space 1}    0.54{col 55}{space 3}0.589{col 63}{space 4}-.1966034{col 76}{space 3} .3460745
{txt}{space 21} {c |}
{space 7}wave#c.threat1 {c |}
survey wave 4 (2016)  {c |}{col 23}{res}{space 2}-.0423713{col 35}{space 2} .0576575{col 46}{space 1}   -0.73{col 55}{space 3}0.463{col 63}{space 4}-.1555394{col 76}{space 3} .0707967
{txt}{space 21} {c |}
{space 15}female {c |}{col 23}{res}{space 2}-.0984533{col 35}{space 2} .0403199{col 46}{space 1}   -2.44{col 55}{space 3}0.015{col 63}{space 4}-.1775916{col 76}{space 3} -.019315
{txt}{space 18}Age {c |}{col 23}{res}{space 2} .0020614{col 35}{space 2} .0022865{col 46}{space 1}    0.90{col 55}{space 3}0.368{col 63}{space 4}-.0024265{col 76}{space 3} .0065494
{txt}{space 14}edu_age {c |}{col 23}{res}{space 2} -.031678{col 35}{space 2} .0136222{col 46}{space 1}   -2.33{col 55}{space 3}0.020{col 63}{space 4}-.0584151{col 76}{space 3}-.0049409
{txt}{space 21} {c |}
{space 10}SocialGrade {c |}
{space 18}C1  {c |}{col 23}{res}{space 2} .0775577{col 35}{space 2}  .050373{col 46}{space 1}    1.54{col 55}{space 3}0.124{col 63}{space 4}-.0213125{col 76}{space 3} .1764279
{txt}{space 18}C2  {c |}{col 23}{res}{space 2} .0989569{col 35}{space 2} .0624588{col 46}{space 1}    1.58{col 55}{space 3}0.113{col 63}{space 4}-.0236348{col 76}{space 3} .2215487
{txt}{space 18}DE  {c |}{col 23}{res}{space 2} .0012693{col 35}{space 2}  .062757{col 46}{space 1}    0.02{col 55}{space 3}0.984{col 63}{space 4}-.1219079{col 76}{space 3} .1244464
{txt}{space 21} {c |}
{space 10}work_status {c |}
{space 3}working part time  {c |}{col 23}{res}{space 2}-.0612208{col 35}{space 2} .0633915{col 46}{space 1}   -0.97{col 55}{space 3}0.334{col 63}{space 4}-.1856433{col 76}{space 3} .0632017
{txt}{space 3}full time student  {c |}{col 23}{res}{space 2}-.3068372{col 35}{space 2} .0845432{col 46}{space 1}   -3.63{col 55}{space 3}0.000{col 63}{space 4}-.4727753{col 76}{space 3}-.1408991
{txt}{space 13}retired  {c |}{col 23}{res}{space 2} .0028307{col 35}{space 2} .0731368{col 46}{space 1}    0.04{col 55}{space 3}0.969{col 63}{space 4}-.1407194{col 76}{space 3} .1463808
{txt}{space 10}unemployed  {c |}{col 23}{res}{space 2} -.003645{col 35}{space 2} .2109954{col 46}{space 1}   -0.02{col 55}{space 3}0.986{col 63}{space 4}-.4177788{col 76}{space 3} .4104888
{txt}{space 9}not working  {c |}{col 23}{res}{space 2}-.0353718{col 35}{space 2} .0693226{col 46}{space 1}   -0.51{col 55}{space 3}0.610{col 63}{space 4}-.1714355{col 76}{space 3} .1006919
{txt}{space 21} {c |}
{space 15}UKborn {c |}{col 23}{res}{space 2}-.3018487{col 35}{space 2} .2205911{col 46}{space 1}   -1.37{col 55}{space 3}0.172{col 63}{space 4}-.7348166{col 76}{space 3} .1311192
{txt}{space 11}authvalues {c |}{col 23}{res}{space 2} .4019588{col 35}{space 2} .0410859{col 46}{space 1}    9.78{col 55}{space 3}0.000{col 63}{space 4} .3213169{col 76}{space 3} .4826007
{txt}{space 14}selfest {c |}{col 23}{res}{space 2} .2197452{col 35}{space 2} .0872974{col 46}{space 1}    2.52{col 55}{space 3}0.012{col 63}{space 4} .0484013{col 76}{space 3} .3910892
{txt}{space 16}_cons {c |}{col 23}{res}{space 2} 1.663094{col 35}{space 2} .4261772{col 46}{space 1}    3.90{col 55}{space 3}0.000{col 63}{space 4} .8266094{col 76}{space 3} 2.499578
{txt}{hline 22}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHblack c.threat2##wave female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest 
{txt}{p}
(system variable _mi_id updated due to changed number of obs.)
{p_end}
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       839

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 799.812814
{txt}{col 1}Number of PSUs{col 19}= {res}      839
{txt}{col 49}Average RVI{col 67}= {res}    0.0000
{txt}{col 49}Largest FMI{col 67}= {res}    0.0000
{txt}{col 49}Complete DF{col 67}= {res}       838
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    836.01
{txt}{col 49}        avg{col 67}= {res}    836.01
{txt}{col 49}        max{col 67}= {res}    836.01
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  17{txt},{res}  836.0{txt}){col 67}= {res}     19.28
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}              GHblack{col 23}{c |}      Coef.{col 35}   Std. Err.{col 47}      t{col 55}   P>|t|{col 63}     [95% Con{col 76}f. Interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 14}threat2 {c |}{col 23}{res}{space 2} .0326331{col 35}{space 2} .0534312{col 46}{space 1}    0.61{col 55}{space 3}0.542{col 63}{space 4}-.0722419{col 76}{space 3} .1375082
{txt}{space 21} {c |}
{space 17}wave {c |}
survey wave 4 (2016)  {c |}{col 23}{res}{space 2} .1766453{col 35}{space 2} .1843736{col 46}{space 1}    0.96{col 55}{space 3}0.338{col 63}{space 4}-.1852443{col 76}{space 3} .5385348
{txt}{space 21} {c |}
{space 7}wave#c.threat2 {c |}
survey wave 4 (2016)  {c |}{col 23}{res}{space 2}-.0808426{col 35}{space 2} .0621993{col 46}{space 1}   -1.30{col 55}{space 3}0.194{col 63}{space 4}-.2029278{col 76}{space 3} .0412426
{txt}{space 21} {c |}
{space 15}female {c |}{col 23}{res}{space 2}-.0694672{col 35}{space 2} .0399601{col 46}{space 1}   -1.74{col 55}{space 3}0.083{col 63}{space 4}-.1479011{col 76}{space 3} .0089668
{txt}{space 18}Age {c |}{col 23}{res}{space 2} .0018902{col 35}{space 2} .0023182{col 46}{space 1}    0.82{col 55}{space 3}0.415{col 63}{space 4}-.0026599{col 76}{space 3} .0064403
{txt}{space 14}edu_age {c |}{col 23}{res}{space 2}-.0237404{col 35}{space 2} .0136448{col 46}{space 1}   -1.74{col 55}{space 3}0.082{col 63}{space 4}-.0505226{col 76}{space 3} .0030418
{txt}{space 21} {c |}
{space 10}SocialGrade {c |}
{space 18}C1  {c |}{col 23}{res}{space 2} .0793664{col 35}{space 2} .0502772{col 46}{space 1}    1.58{col 55}{space 3}0.115{col 63}{space 4} -.019318{col 76}{space 3} .1780508
{txt}{space 18}C2  {c |}{col 23}{res}{space 2} .1005226{col 35}{space 2}  .061696{col 46}{space 1}    1.63{col 55}{space 3}0.104{col 63}{space 4}-.0205747{col 76}{space 3} .2216198
{txt}{space 18}DE  {c |}{col 23}{res}{space 2} .0031551{col 35}{space 2} .0622961{col 46}{space 1}    0.05{col 55}{space 3}0.960{col 63}{space 4}  -.11912{col 76}{space 3} .1254302
{txt}{space 21} {c |}
{space 10}work_status {c |}
{space 3}working part time  {c |}{col 23}{res}{space 2}-.0628444{col 35}{space 2} .0627985{col 46}{space 1}   -1.00{col 55}{space 3}0.317{col 63}{space 4}-.1861055{col 76}{space 3} .0604168
{txt}{space 3}full time student  {c |}{col 23}{res}{space 2}-.3037816{col 35}{space 2} .0854021{col 46}{space 1}   -3.56{col 55}{space 3}0.000{col 63}{space 4}-.4714094{col 76}{space 3}-.1361538
{txt}{space 13}retired  {c |}{col 23}{res}{space 2} .0132835{col 35}{space 2} .0714763{col 46}{space 1}    0.19{col 55}{space 3}0.853{col 63}{space 4}-.1270105{col 76}{space 3} .1535776
{txt}{space 10}unemployed  {c |}{col 23}{res}{space 2} .0124682{col 35}{space 2} .2076041{col 46}{space 1}    0.06{col 55}{space 3}0.952{col 63}{space 4}-.3950184{col 76}{space 3} .4199547
{txt}{space 9}not working  {c |}{col 23}{res}{space 2}-.0155437{col 35}{space 2} .0702737{col 46}{space 1}   -0.22{col 55}{space 3}0.825{col 63}{space 4}-.1534774{col 76}{space 3}   .12239
{txt}{space 21} {c |}
{space 15}UKborn {c |}{col 23}{res}{space 2}-.2734554{col 35}{space 2} .2535347{col 46}{space 1}   -1.08{col 55}{space 3}0.281{col 63}{space 4}-.7710947{col 76}{space 3} .2241839
{txt}{space 11}authvalues {c |}{col 23}{res}{space 2} .4305025{col 35}{space 2} .0399815{col 46}{space 1}   10.77{col 55}{space 3}0.000{col 63}{space 4} .3520267{col 76}{space 3} .5089784
{txt}{space 14}selfest {c |}{col 23}{res}{space 2} .3043771{col 35}{space 2} .0824568{col 46}{space 1}    3.69{col 55}{space 3}0.000{col 63}{space 4} .1425303{col 76}{space 3} .4662238
{txt}{space 16}_cons {c |}{col 23}{res}{space 2} 1.562352{col 35}{space 2}  .467672{col 46}{space 1}    3.34{col 55}{space 3}0.001{col 63}{space 4} .6444023{col 76}{space 3} 2.480301
{txt}{hline 22}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHblack c.threat3##wave female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest 
{txt}{p}
(system variable _mi_id updated due to changed number of obs.)
{p_end}
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       857

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 819.364102
{txt}{col 1}Number of PSUs{col 19}= {res}      857
{txt}{col 49}Average RVI{col 67}= {res}    0.0000
{txt}{col 49}Largest FMI{col 67}= {res}    0.0000
{txt}{col 49}Complete DF{col 67}= {res}       856
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    854.01
{txt}{col 49}        avg{col 67}= {res}    854.01
{txt}{col 49}        max{col 67}= {res}    854.01
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  17{txt},{res}  854.0{txt}){col 67}= {res}     19.09
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}              GHblack{col 23}{c |}      Coef.{col 35}   Std. Err.{col 47}      t{col 55}   P>|t|{col 63}     [95% Con{col 76}f. Interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 14}threat3 {c |}{col 23}{res}{space 2} .0604317{col 35}{space 2} .0483595{col 46}{space 1}    1.25{col 55}{space 3}0.212{col 63}{space 4}-.0344856{col 76}{space 3} .1553491
{txt}{space 21} {c |}
{space 17}wave {c |}
survey wave 4 (2016)  {c |}{col 23}{res}{space 2}-.1255662{col 35}{space 2} .1651901{col 46}{space 1}   -0.76{col 55}{space 3}0.447{col 63}{space 4}-.4497924{col 76}{space 3} .1986599
{txt}{space 21} {c |}
{space 7}wave#c.threat3 {c |}
survey wave 4 (2016)  {c |}{col 23}{res}{space 2} .0279951{col 35}{space 2} .0583484{col 46}{space 1}    0.48{col 55}{space 3}0.631{col 63}{space 4}-.0865279{col 76}{space 3} .1425181
{txt}{space 21} {c |}
{space 15}female {c |}{col 23}{res}{space 2}-.1035673{col 35}{space 2} .0401938{col 46}{space 1}   -2.58{col 55}{space 3}0.010{col 63}{space 4}-.1824575{col 76}{space 3} -.024677
{txt}{space 18}Age {c |}{col 23}{res}{space 2}   .00217{col 35}{space 2} .0022394{col 46}{space 1}    0.97{col 55}{space 3}0.333{col 63}{space 4}-.0022255{col 76}{space 3} .0065654
{txt}{space 14}edu_age {c |}{col 23}{res}{space 2}-.0315312{col 35}{space 2} .0137192{col 46}{space 1}   -2.30{col 55}{space 3}0.022{col 63}{space 4}-.0584584{col 76}{space 3}-.0046039
{txt}{space 21} {c |}
{space 10}SocialGrade {c |}
{space 18}C1  {c |}{col 23}{res}{space 2} .0810067{col 35}{space 2} .0504591{col 46}{space 1}    1.61{col 55}{space 3}0.109{col 63}{space 4}-.0180316{col 76}{space 3}  .180045
{txt}{space 18}C2  {c |}{col 23}{res}{space 2} .1053916{col 35}{space 2} .0620157{col 46}{space 1}    1.70{col 55}{space 3}0.090{col 63}{space 4}-.0163294{col 76}{space 3} .2271127
{txt}{space 18}DE  {c |}{col 23}{res}{space 2}  .004353{col 35}{space 2} .0603457{col 46}{space 1}    0.07{col 55}{space 3}0.943{col 63}{space 4}-.1140902{col 76}{space 3} .1227962
{txt}{space 21} {c |}
{space 10}work_status {c |}
{space 3}working part time  {c |}{col 23}{res}{space 2}-.0618941{col 35}{space 2} .0636818{col 46}{space 1}   -0.97{col 55}{space 3}0.331{col 63}{space 4}-.1868854{col 76}{space 3} .0630971
{txt}{space 3}full time student  {c |}{col 23}{res}{space 2}-.3022039{col 35}{space 2} .0847487{col 46}{space 1}   -3.57{col 55}{space 3}0.000{col 63}{space 4} -.468544{col 76}{space 3}-.1358637
{txt}{space 13}retired  {c |}{col 23}{res}{space 2}-.0107887{col 35}{space 2} .0728084{col 46}{space 1}   -0.15{col 55}{space 3}0.882{col 63}{space 4}-.1536931{col 76}{space 3} .1321157
{txt}{space 10}unemployed  {c |}{col 23}{res}{space 2}-.0218855{col 35}{space 2} .2119957{col 46}{space 1}   -0.10{col 55}{space 3}0.918{col 63}{space 4}-.4379792{col 76}{space 3} .3942082
{txt}{space 9}not working  {c |}{col 23}{res}{space 2}  -.03527{col 35}{space 2} .0684893{col 46}{space 1}   -0.51{col 55}{space 3}0.607{col 63}{space 4}-.1696972{col 76}{space 3} .0991571
{txt}{space 21} {c |}
{space 15}UKborn {c |}{col 23}{res}{space 2}-.2977308{col 35}{space 2} .2293295{col 46}{space 1}   -1.30{col 55}{space 3}0.195{col 63}{space 4}-.7478462{col 76}{space 3} .1523847
{txt}{space 11}authvalues {c |}{col 23}{res}{space 2} .4075747{col 35}{space 2} .0408041{col 46}{space 1}    9.99{col 55}{space 3}0.000{col 63}{space 4} .3274867{col 76}{space 3} .4876626
{txt}{space 14}selfest {c |}{col 23}{res}{space 2} .2416461{col 35}{space 2} .0842129{col 46}{space 1}    2.87{col 55}{space 3}0.004{col 63}{space 4} .0763575{col 76}{space 3} .4069347
{txt}{space 16}_cons {c |}{col 23}{res}{space 2} 1.739814{col 35}{space 2} .4397403{col 46}{space 1}    3.96{col 55}{space 3}0.000{col 63}{space 4} .8767151{col 76}{space 3} 2.602912
{txt}{hline 22}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHblack c.threat4##wave female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest 
{txt}{p}
(system variable _mi_id updated due to changed number of obs.)
{p_end}
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       851

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 813.303368
{txt}{col 1}Number of PSUs{col 19}= {res}      851
{txt}{col 49}Average RVI{col 67}= {res}    0.0000
{txt}{col 49}Largest FMI{col 67}= {res}    0.0000
{txt}{col 49}Complete DF{col 67}= {res}       850
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    848.01
{txt}{col 49}        avg{col 67}= {res}    848.01
{txt}{col 49}        max{col 67}= {res}    848.01
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  17{txt},{res}  848.0{txt}){col 67}= {res}     28.75
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}              GHblack{col 23}{c |}      Coef.{col 35}   Std. Err.{col 47}      t{col 55}   P>|t|{col 63}     [95% Con{col 76}f. Interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 14}threat4 {c |}{col 23}{res}{space 2} .1929405{col 35}{space 2}  .034716{col 46}{space 1}    5.56{col 55}{space 3}0.000{col 63}{space 4} .1248012{col 76}{space 3} .2610797
{txt}{space 21} {c |}
{space 17}wave {c |}
survey wave 4 (2016)  {c |}{col 23}{res}{space 2}-.1068539{col 35}{space 2} .1178797{col 46}{space 1}   -0.91{col 55}{space 3}0.365{col 63}{space 4}-.3382241{col 76}{space 3} .1245163
{txt}{space 21} {c |}
{space 7}wave#c.threat4 {c |}
survey wave 4 (2016)  {c |}{col 23}{res}{space 2} .0404101{col 35}{space 2} .0419508{col 46}{space 1}    0.96{col 55}{space 3}0.336{col 63}{space 4}-.0419295{col 76}{space 3} .1227497
{txt}{space 21} {c |}
{space 15}female {c |}{col 23}{res}{space 2}-.0977425{col 35}{space 2} .0380699{col 46}{space 1}   -2.57{col 55}{space 3}0.010{col 63}{space 4}-.1724648{col 76}{space 3}-.0230201
{txt}{space 18}Age {c |}{col 23}{res}{space 2}-.0014631{col 35}{space 2} .0021436{col 46}{space 1}   -0.68{col 55}{space 3}0.495{col 63}{space 4}-.0056704{col 76}{space 3} .0027442
{txt}{space 14}edu_age {c |}{col 23}{res}{space 2}-.0151536{col 35}{space 2} .0133152{col 46}{space 1}   -1.14{col 55}{space 3}0.255{col 63}{space 4}-.0412883{col 76}{space 3} .0109811
{txt}{space 21} {c |}
{space 10}SocialGrade {c |}
{space 18}C1  {c |}{col 23}{res}{space 2} .0272249{col 35}{space 2}  .049076{col 46}{space 1}    0.55{col 55}{space 3}0.579{col 63}{space 4}-.0690997{col 76}{space 3} .1235496
{txt}{space 18}C2  {c |}{col 23}{res}{space 2} .0601442{col 35}{space 2} .0583805{col 46}{space 1}    1.03{col 55}{space 3}0.303{col 63}{space 4} -.054443{col 76}{space 3} .1747313
{txt}{space 18}DE  {c |}{col 23}{res}{space 2}-.0398468{col 35}{space 2} .0585506{col 46}{space 1}   -0.68{col 55}{space 3}0.496{col 63}{space 4}-.1547679{col 76}{space 3} .0750744
{txt}{space 21} {c |}
{space 10}work_status {c |}
{space 3}working part time  {c |}{col 23}{res}{space 2}-.0345456{col 35}{space 2} .0619953{col 46}{space 1}   -0.56{col 55}{space 3}0.578{col 63}{space 4}-.1562278{col 76}{space 3} .0871366
{txt}{space 3}full time student  {c |}{col 23}{res}{space 2}-.2508572{col 35}{space 2}  .082669{col 46}{space 1}   -3.03{col 55}{space 3}0.002{col 63}{space 4} -.413117{col 76}{space 3}-.0885973
{txt}{space 13}retired  {c |}{col 23}{res}{space 2}  .037012{col 35}{space 2}   .06809{col 46}{space 1}    0.54{col 55}{space 3}0.587{col 63}{space 4}-.0966327{col 76}{space 3} .1706567
{txt}{space 10}unemployed  {c |}{col 23}{res}{space 2}-.0386802{col 35}{space 2} .1997404{col 46}{space 1}   -0.19{col 55}{space 3}0.846{col 63}{space 4}-.4307236{col 76}{space 3} .3533633
{txt}{space 9}not working  {c |}{col 23}{res}{space 2}-.0184703{col 35}{space 2} .0630793{col 46}{space 1}   -0.29{col 55}{space 3}0.770{col 63}{space 4}-.1422801{col 76}{space 3} .1053395
{txt}{space 21} {c |}
{space 15}UKborn {c |}{col 23}{res}{space 2} -.360453{col 35}{space 2}  .155574{col 46}{space 1}   -2.32{col 55}{space 3}0.021{col 63}{space 4}-.6658082{col 76}{space 3}-.0550978
{txt}{space 11}authvalues {c |}{col 23}{res}{space 2} .3342749{col 35}{space 2} .0409234{col 46}{space 1}    8.17{col 55}{space 3}0.000{col 63}{space 4} .2539519{col 76}{space 3} .4145979
{txt}{space 14}selfest {c |}{col 23}{res}{space 2} .1824327{col 35}{space 2} .0798149{col 46}{space 1}    2.29{col 55}{space 3}0.023{col 63}{space 4} .0257748{col 76}{space 3} .3390906
{txt}{space 16}_cons {c |}{col 23}{res}{space 2} 1.467432{col 35}{space 2} .3803105{col 46}{space 1}    3.86{col 55}{space 3}0.000{col 63}{space 4} .7209716{col 76}{space 3} 2.213892
{txt}{hline 22}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHblack c.threat5##wave female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest 
{txt}{p}
(system variable _mi_id updated due to changed number of obs.)
{p_end}
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       842

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 804.333307
{txt}{col 1}Number of PSUs{col 19}= {res}      842
{txt}{col 49}Average RVI{col 67}= {res}    0.0000
{txt}{col 49}Largest FMI{col 67}= {res}    0.0000
{txt}{col 49}Complete DF{col 67}= {res}       841
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    839.01
{txt}{col 49}        avg{col 67}= {res}    839.01
{txt}{col 49}        max{col 67}= {res}    839.01
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  17{txt},{res}  839.0{txt}){col 67}= {res}     19.43
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}              GHblack{col 23}{c |}      Coef.{col 35}   Std. Err.{col 47}      t{col 55}   P>|t|{col 63}     [95% Con{col 76}f. Interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 14}threat5 {c |}{col 23}{res}{space 2}-.0098129{col 35}{space 2} .0551319{col 46}{space 1}   -0.18{col 55}{space 3}0.859{col 63}{space 4}-.1180256{col 76}{space 3} .0983997
{txt}{space 21} {c |}
{space 17}wave {c |}
survey wave 4 (2016)  {c |}{col 23}{res}{space 2} .1905503{col 35}{space 2} .2033653{col 46}{space 1}    0.94{col 55}{space 3}0.349{col 63}{space 4}-.2086141{col 76}{space 3} .5897147
{txt}{space 21} {c |}
{space 7}wave#c.threat5 {c |}
survey wave 4 (2016)  {c |}{col 23}{res}{space 2}-.0926145{col 35}{space 2} .0645126{col 46}{space 1}   -1.44{col 55}{space 3}0.151{col 63}{space 4}-.2192395{col 76}{space 3} .0340105
{txt}{space 21} {c |}
{space 15}female {c |}{col 23}{res}{space 2}-.0785241{col 35}{space 2} .0408244{col 46}{space 1}   -1.92{col 55}{space 3}0.055{col 63}{space 4} -.158654{col 76}{space 3} .0016058
{txt}{space 18}Age {c |}{col 23}{res}{space 2} .0016967{col 35}{space 2} .0023336{col 46}{space 1}    0.73{col 55}{space 3}0.467{col 63}{space 4}-.0028837{col 76}{space 3} .0062772
{txt}{space 14}edu_age {c |}{col 23}{res}{space 2}-.0296509{col 35}{space 2} .0140017{col 46}{space 1}   -2.12{col 55}{space 3}0.034{col 63}{space 4}-.0571332{col 76}{space 3}-.0021685
{txt}{space 21} {c |}
{space 10}SocialGrade {c |}
{space 18}C1  {c |}{col 23}{res}{space 2}  .095558{col 35}{space 2} .0513791{col 46}{space 1}    1.86{col 55}{space 3}0.063{col 63}{space 4}-.0052886{col 76}{space 3} .1964045
{txt}{space 18}C2  {c |}{col 23}{res}{space 2} .0925246{col 35}{space 2} .0631542{col 46}{space 1}    1.47{col 55}{space 3}0.143{col 63}{space 4}-.0314341{col 76}{space 3} .2164833
{txt}{space 18}DE  {c |}{col 23}{res}{space 2}-.0033357{col 35}{space 2} .0624243{col 46}{space 1}   -0.05{col 55}{space 3}0.957{col 63}{space 4}-.1258618{col 76}{space 3} .1191904
{txt}{space 21} {c |}
{space 10}work_status {c |}
{space 3}working part time  {c |}{col 23}{res}{space 2} -.078057{col 35}{space 2} .0626273{col 46}{space 1}   -1.25{col 55}{space 3}0.213{col 63}{space 4}-.2009815{col 76}{space 3} .0448675
{txt}{space 3}full time student  {c |}{col 23}{res}{space 2}-.3120802{col 35}{space 2} .0851119{col 46}{space 1}   -3.67{col 55}{space 3}0.000{col 63}{space 4}-.4791375{col 76}{space 3} -.145023
{txt}{space 13}retired  {c |}{col 23}{res}{space 2}-.0084765{col 35}{space 2} .0738769{col 46}{space 1}   -0.11{col 55}{space 3}0.909{col 63}{space 4}-.1534817{col 76}{space 3} .1365287
{txt}{space 10}unemployed  {c |}{col 23}{res}{space 2}-.0299427{col 35}{space 2} .2132851{col 46}{space 1}   -0.14{col 55}{space 3}0.888{col 63}{space 4}-.4485777{col 76}{space 3} .3886924
{txt}{space 9}not working  {c |}{col 23}{res}{space 2}-.0572099{col 35}{space 2} .0718749{col 46}{space 1}   -0.80{col 55}{space 3}0.426{col 63}{space 4}-.1982857{col 76}{space 3} .0838659
{txt}{space 21} {c |}
{space 15}UKborn {c |}{col 23}{res}{space 2}-.2600724{col 35}{space 2} .2059697{col 46}{space 1}   -1.26{col 55}{space 3}0.207{col 63}{space 4}-.6643488{col 76}{space 3} .1442041
{txt}{space 11}authvalues {c |}{col 23}{res}{space 2} .3946377{col 35}{space 2} .0415922{col 46}{space 1}    9.49{col 55}{space 3}0.000{col 63}{space 4} .3130006{col 76}{space 3} .4762747
{txt}{space 14}selfest {c |}{col 23}{res}{space 2} .2868636{col 35}{space 2} .0866089{col 46}{space 1}    3.31{col 55}{space 3}0.001{col 63}{space 4} .1168681{col 76}{space 3} .4568592
{txt}{space 16}_cons {c |}{col 23}{res}{space 2}  1.90027{col 35}{space 2} .4434456{col 46}{space 1}    4.29{col 55}{space 3}0.000{col 63}{space 4} 1.029877{col 76}{space 3} 2.770663
{txt}{hline 22}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. mi estimate: svy: reg GHMus c.threat1##wave female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest 
{txt}{p}
(system variable _mi_id updated due to changed number of obs.)
{p_end}
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       826

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 788.488652
{txt}{col 1}Number of PSUs{col 19}= {res}      826
{txt}{col 49}Average RVI{col 67}= {res}    0.0000
{txt}{col 49}Largest FMI{col 67}= {res}    0.0000
{txt}{col 49}Complete DF{col 67}= {res}       825
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    823.01
{txt}{col 49}        avg{col 67}= {res}    823.01
{txt}{col 49}        max{col 67}= {res}    823.01
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  17{txt},{res}  823.0{txt}){col 67}= {res}     20.33
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}                GHMus{col 23}{c |}      Coef.{col 35}   Std. Err.{col 47}      t{col 55}   P>|t|{col 63}     [95% Con{col 76}f. Interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 14}threat1 {c |}{col 23}{res}{space 2} .1191717{col 35}{space 2} .0579838{col 46}{space 1}    2.06{col 55}{space 3}0.040{col 63}{space 4} .0053582{col 76}{space 3} .2329853
{txt}{space 21} {c |}
{space 17}wave {c |}
survey wave 4 (2016)  {c |}{col 23}{res}{space 2}-.0472656{col 35}{space 2} .1595239{col 46}{space 1}   -0.30{col 55}{space 3}0.767{col 63}{space 4}-.3603871{col 76}{space 3}  .265856
{txt}{space 21} {c |}
{space 7}wave#c.threat1 {c |}
survey wave 4 (2016)  {c |}{col 23}{res}{space 2}-.0084284{col 35}{space 2} .0682966{col 46}{space 1}   -0.12{col 55}{space 3}0.902{col 63}{space 4}-.1424844{col 76}{space 3} .1256276
{txt}{space 21} {c |}
{space 15}female {c |}{col 23}{res}{space 2}-.1068661{col 35}{space 2}  .046547{col 46}{space 1}   -2.30{col 55}{space 3}0.022{col 63}{space 4} -.198231{col 76}{space 3}-.0155012
{txt}{space 18}Age {c |}{col 23}{res}{space 2} .0050881{col 35}{space 2}  .002253{col 46}{space 1}    2.26{col 55}{space 3}0.024{col 63}{space 4} .0006657{col 76}{space 3} .0095104
{txt}{space 14}edu_age {c |}{col 23}{res}{space 2}-.0539769{col 35}{space 2} .0151163{col 46}{space 1}   -3.57{col 55}{space 3}0.000{col 63}{space 4}-.0836479{col 76}{space 3}-.0243058
{txt}{space 21} {c |}
{space 10}SocialGrade {c |}
{space 18}C1  {c |}{col 23}{res}{space 2}-.0059374{col 35}{space 2} .0543014{col 46}{space 1}   -0.11{col 55}{space 3}0.913{col 63}{space 4}-.1125229{col 76}{space 3} .1006482
{txt}{space 18}C2  {c |}{col 23}{res}{space 2} .1596708{col 35}{space 2} .0778719{col 46}{space 1}    2.05{col 55}{space 3}0.041{col 63}{space 4} .0068198{col 76}{space 3} .3125218
{txt}{space 18}DE  {c |}{col 23}{res}{space 2}-.0012756{col 35}{space 2}  .075954{col 46}{space 1}   -0.02{col 55}{space 3}0.987{col 63}{space 4}-.1503619{col 76}{space 3} .1478106
{txt}{space 21} {c |}
{space 10}work_status {c |}
{space 3}working part time  {c |}{col 23}{res}{space 2}-.1073493{col 35}{space 2} .0666126{col 46}{space 1}   -1.61{col 55}{space 3}0.107{col 63}{space 4}   -.2381{col 76}{space 3} .0234013
{txt}{space 3}full time student  {c |}{col 23}{res}{space 2}-.2310942{col 35}{space 2} .1090686{col 46}{space 1}   -2.12{col 55}{space 3}0.034{col 63}{space 4}-.4451796{col 76}{space 3}-.0170089
{txt}{space 13}retired  {c |}{col 23}{res}{space 2} -.116197{col 35}{space 2} .0785219{col 46}{space 1}   -1.48{col 55}{space 3}0.139{col 63}{space 4}-.2703236{col 76}{space 3} .0379297
{txt}{space 10}unemployed  {c |}{col 23}{res}{space 2} .3950668{col 35}{space 2} .2044652{col 46}{space 1}    1.93{col 55}{space 3}0.054{col 63}{space 4}-.0062679{col 76}{space 3} .7964015
{txt}{space 9}not working  {c |}{col 23}{res}{space 2}-.0649134{col 35}{space 2}  .092169{col 46}{space 1}   -0.70{col 55}{space 3}0.481{col 63}{space 4}-.2458275{col 76}{space 3} .1160006
{txt}{space 21} {c |}
{space 15}UKborn {c |}{col 23}{res}{space 2}-.1579308{col 35}{space 2} .2961348{col 46}{space 1}   -0.53{col 55}{space 3}0.594{col 63}{space 4}-.7391992{col 76}{space 3} .4233377
{txt}{space 11}authvalues {c |}{col 23}{res}{space 2} .3742448{col 35}{space 2} .0463172{col 46}{space 1}    8.08{col 55}{space 3}0.000{col 63}{space 4}  .283331{col 76}{space 3} .4651585
{txt}{space 14}selfest {c |}{col 23}{res}{space 2} .3033173{col 35}{space 2} .0946855{col 46}{space 1}    3.20{col 55}{space 3}0.001{col 63}{space 4} .1174639{col 76}{space 3} .4891707
{txt}{space 16}_cons {c |}{col 23}{res}{space 2} 1.953811{col 35}{space 2} .4943617{col 46}{space 1}    3.95{col 55}{space 3}0.000{col 63}{space 4} .9834527{col 76}{space 3} 2.924169
{txt}{hline 22}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHMus c.threat2##wave female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest 
{txt}{p}
(system variable _mi_id updated due to changed number of obs.)
{p_end}
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       812

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res}  774.01314
{txt}{col 1}Number of PSUs{col 19}= {res}      812
{txt}{col 49}Average RVI{col 67}= {res}    0.0000
{txt}{col 49}Largest FMI{col 67}= {res}    0.0000
{txt}{col 49}Complete DF{col 67}= {res}       811
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    809.01
{txt}{col 49}        avg{col 67}= {res}    809.01
{txt}{col 49}        max{col 67}= {res}    809.01
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  17{txt},{res}  809.0{txt}){col 67}= {res}     20.12
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}                GHMus{col 23}{c |}      Coef.{col 35}   Std. Err.{col 47}      t{col 55}   P>|t|{col 63}     [95% Con{col 76}f. Interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 14}threat2 {c |}{col 23}{res}{space 2} .0593573{col 35}{space 2} .0635685{col 46}{space 1}    0.93{col 55}{space 3}0.351{col 63}{space 4}-.0654214{col 76}{space 3} .1841359
{txt}{space 21} {c |}
{space 17}wave {c |}
survey wave 4 (2016)  {c |}{col 23}{res}{space 2} .2823049{col 35}{space 2} .2159838{col 46}{space 1}    1.31{col 55}{space 3}0.192{col 63}{space 4}-.1416497{col 76}{space 3} .7062596
{txt}{space 21} {c |}
{space 7}wave#c.threat2 {c |}
survey wave 4 (2016)  {c |}{col 23}{res}{space 2}-.1351233{col 35}{space 2} .0720679{col 46}{space 1}   -1.87{col 55}{space 3}0.061{col 63}{space 4}-.2765855{col 76}{space 3} .0063389
{txt}{space 21} {c |}
{space 15}female {c |}{col 23}{res}{space 2}-.0862042{col 35}{space 2} .0478245{col 46}{space 1}   -1.80{col 55}{space 3}0.072{col 63}{space 4} -.180079{col 76}{space 3} .0076706
{txt}{space 18}Age {c |}{col 23}{res}{space 2} .0049224{col 35}{space 2}  .002302{col 46}{space 1}    2.14{col 55}{space 3}0.033{col 63}{space 4} .0004039{col 76}{space 3}  .009441
{txt}{space 14}edu_age {c |}{col 23}{res}{space 2}-.0482825{col 35}{space 2} .0155902{col 46}{space 1}   -3.10{col 55}{space 3}0.002{col 63}{space 4}-.0788845{col 76}{space 3}-.0176804
{txt}{space 21} {c |}
{space 10}SocialGrade {c |}
{space 18}C1  {c |}{col 23}{res}{space 2} .0194409{col 35}{space 2} .0555312{col 46}{space 1}    0.35{col 55}{space 3}0.726{col 63}{space 4}-.0895613{col 76}{space 3} .1284431
{txt}{space 18}C2  {c |}{col 23}{res}{space 2} .1829279{col 35}{space 2} .0784759{col 46}{space 1}    2.33{col 55}{space 3}0.020{col 63}{space 4} .0288875{col 76}{space 3} .3369682
{txt}{space 18}DE  {c |}{col 23}{res}{space 2} .0316468{col 35}{space 2} .0762482{col 46}{space 1}    0.42{col 55}{space 3}0.678{col 63}{space 4}-.1180209{col 76}{space 3} .1813146
{txt}{space 21} {c |}
{space 10}work_status {c |}
{space 3}working part time  {c |}{col 23}{res}{space 2}-.1285508{col 35}{space 2} .0687496{col 46}{space 1}   -1.87{col 55}{space 3}0.062{col 63}{space 4}-.2634994{col 76}{space 3} .0063978
{txt}{space 3}full time student  {c |}{col 23}{res}{space 2}-.2130407{col 35}{space 2} .1089518{col 46}{space 1}   -1.96{col 55}{space 3}0.051{col 63}{space 4}-.4269024{col 76}{space 3} .0008209
{txt}{space 13}retired  {c |}{col 23}{res}{space 2}-.1220625{col 35}{space 2} .0791969{col 46}{space 1}   -1.54{col 55}{space 3}0.124{col 63}{space 4}-.2775181{col 76}{space 3}  .033393
{txt}{space 10}unemployed  {c |}{col 23}{res}{space 2} .4017496{col 35}{space 2} .2176033{col 46}{space 1}    1.85{col 55}{space 3}0.065{col 63}{space 4} -.025384{col 76}{space 3} .8288832
{txt}{space 9}not working  {c |}{col 23}{res}{space 2}-.0708878{col 35}{space 2} .0938223{col 46}{space 1}   -0.76{col 55}{space 3}0.450{col 63}{space 4}-.2550516{col 76}{space 3}  .113276
{txt}{space 21} {c |}
{space 15}UKborn {c |}{col 23}{res}{space 2}-.0717811{col 35}{space 2} .3332228{col 46}{space 1}   -0.22{col 55}{space 3}0.829{col 63}{space 4}-.7258642{col 76}{space 3} .5823021
{txt}{space 11}authvalues {c |}{col 23}{res}{space 2} .3963387{col 35}{space 2} .0475958{col 46}{space 1}    8.33{col 55}{space 3}0.000{col 63}{space 4} .3029129{col 76}{space 3} .4897645
{txt}{space 14}selfest {c |}{col 23}{res}{space 2} .4343705{col 35}{space 2} .0956721{col 46}{space 1}    4.54{col 55}{space 3}0.000{col 63}{space 4} .2465757{col 76}{space 3} .6221654
{txt}{space 16}_cons {c |}{col 23}{res}{space 2} 1.779774{col 35}{space 2} .5585564{col 46}{space 1}    3.19{col 55}{space 3}0.001{col 63}{space 4} .6833832{col 76}{space 3} 2.876165
{txt}{hline 22}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHMus c.threat3##wave female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest 
{txt}{p}
(system variable _mi_id updated due to changed number of obs.)
{p_end}
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       829

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 791.308578
{txt}{col 1}Number of PSUs{col 19}= {res}      829
{txt}{col 49}Average RVI{col 67}= {res}    0.0000
{txt}{col 49}Largest FMI{col 67}= {res}    0.0000
{txt}{col 49}Complete DF{col 67}= {res}       828
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    826.01
{txt}{col 49}        avg{col 67}= {res}    826.01
{txt}{col 49}        max{col 67}= {res}    826.01
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  17{txt},{res}  826.0{txt}){col 67}= {res}     19.77
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}                GHMus{col 23}{c |}      Coef.{col 35}   Std. Err.{col 47}      t{col 55}   P>|t|{col 63}     [95% Con{col 76}f. Interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 14}threat3 {c |}{col 23}{res}{space 2} .0870506{col 35}{space 2} .0485077{col 46}{space 1}    1.79{col 55}{space 3}0.073{col 63}{space 4}-.0081623{col 76}{space 3} .1822634
{txt}{space 21} {c |}
{space 17}wave {c |}
survey wave 4 (2016)  {c |}{col 23}{res}{space 2}-.0441823{col 35}{space 2} .1673747{col 46}{space 1}   -0.26{col 55}{space 3}0.792{col 63}{space 4}-.3727121{col 76}{space 3} .2843474
{txt}{space 21} {c |}
{space 7}wave#c.threat3 {c |}
survey wave 4 (2016)  {c |}{col 23}{res}{space 2}-.0150199{col 35}{space 2} .0603689{col 46}{space 1}   -0.25{col 55}{space 3}0.804{col 63}{space 4}-.1335144{col 76}{space 3} .1034745
{txt}{space 21} {c |}
{space 15}female {c |}{col 23}{res}{space 2}-.1083034{col 35}{space 2} .0473659{col 46}{space 1}   -2.29{col 55}{space 3}0.022{col 63}{space 4} -.201275{col 76}{space 3}-.0153317
{txt}{space 18}Age {c |}{col 23}{res}{space 2}  .005192{col 35}{space 2} .0022619{col 46}{space 1}    2.30{col 55}{space 3}0.022{col 63}{space 4} .0007522{col 76}{space 3} .0096317
{txt}{space 14}edu_age {c |}{col 23}{res}{space 2}-.0522172{col 35}{space 2} .0152166{col 46}{space 1}   -3.43{col 55}{space 3}0.001{col 63}{space 4}-.0820849{col 76}{space 3}-.0223496
{txt}{space 21} {c |}
{space 10}SocialGrade {c |}
{space 18}C1  {c |}{col 23}{res}{space 2} .0052734{col 35}{space 2} .0548688{col 46}{space 1}    0.10{col 55}{space 3}0.923{col 63}{space 4}-.1024253{col 76}{space 3} .1129721
{txt}{space 18}C2  {c |}{col 23}{res}{space 2} .1694632{col 35}{space 2}  .078364{col 46}{space 1}    2.16{col 55}{space 3}0.031{col 63}{space 4} .0156471{col 76}{space 3} .3232792
{txt}{space 18}DE  {c |}{col 23}{res}{space 2} .0100153{col 35}{space 2}  .074645{col 46}{space 1}    0.13{col 55}{space 3}0.893{col 63}{space 4}-.1365008{col 76}{space 3} .1565314
{txt}{space 21} {c |}
{space 10}work_status {c |}
{space 3}working part time  {c |}{col 23}{res}{space 2}-.1055563{col 35}{space 2} .0683982{col 46}{space 1}   -1.54{col 55}{space 3}0.123{col 63}{space 4} -.239811{col 76}{space 3} .0286983
{txt}{space 3}full time student  {c |}{col 23}{res}{space 2} -.204296{col 35}{space 2} .1106475{col 46}{space 1}   -1.85{col 55}{space 3}0.065{col 63}{space 4}-.4214793{col 76}{space 3} .0128874
{txt}{space 13}retired  {c |}{col 23}{res}{space 2}-.1364108{col 35}{space 2} .0784459{col 46}{space 1}   -1.74{col 55}{space 3}0.082{col 63}{space 4}-.2903877{col 76}{space 3}  .017566
{txt}{space 10}unemployed  {c |}{col 23}{res}{space 2} .4024709{col 35}{space 2} .2154172{col 46}{space 1}    1.87{col 55}{space 3}0.062{col 63}{space 4}-.0203585{col 76}{space 3} .8253004
{txt}{space 9}not working  {c |}{col 23}{res}{space 2}-.0740791{col 35}{space 2} .0921211{col 46}{space 1}   -0.80{col 55}{space 3}0.422{col 63}{space 4} -.254898{col 76}{space 3} .1067398
{txt}{space 21} {c |}
{space 15}UKborn {c |}{col 23}{res}{space 2}-.1316875{col 35}{space 2} .3010831{col 46}{space 1}   -0.44{col 55}{space 3}0.662{col 63}{space 4}-.7226655{col 76}{space 3} .4592906
{txt}{space 11}authvalues {c |}{col 23}{res}{space 2} .3924886{col 35}{space 2} .0469338{col 46}{space 1}    8.36{col 55}{space 3}0.000{col 63}{space 4} .3003649{col 76}{space 3} .4846122
{txt}{space 14}selfest {c |}{col 23}{res}{space 2} .3529853{col 35}{space 2} .0917914{col 46}{space 1}    3.85{col 55}{space 3}0.000{col 63}{space 4} .1728135{col 76}{space 3} .5331571
{txt}{space 16}_cons {c |}{col 23}{res}{space 2} 1.874151{col 35}{space 2} .4958232{col 46}{space 1}    3.78{col 55}{space 3}0.000{col 63}{space 4} .9009297{col 76}{space 3} 2.847373
{txt}{hline 22}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHMus c.threat4##wave female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest 
{txt}{p}
(system variable _mi_id updated due to changed number of obs.)
{p_end}
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       824

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 786.176732
{txt}{col 1}Number of PSUs{col 19}= {res}      824
{txt}{col 49}Average RVI{col 67}= {res}    0.0000
{txt}{col 49}Largest FMI{col 67}= {res}    0.0000
{txt}{col 49}Complete DF{col 67}= {res}       823
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    821.01
{txt}{col 49}        avg{col 67}= {res}    821.01
{txt}{col 49}        max{col 67}= {res}    821.01
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  17{txt},{res}  821.0{txt}){col 67}= {res}     33.67
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}                GHMus{col 23}{c |}      Coef.{col 35}   Std. Err.{col 47}      t{col 55}   P>|t|{col 63}     [95% Con{col 76}f. Interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 14}threat4 {c |}{col 23}{res}{space 2} .2714032{col 35}{space 2} .0436384{col 46}{space 1}    6.22{col 55}{space 3}0.000{col 63}{space 4} .1857473{col 76}{space 3} .3570592
{txt}{space 21} {c |}
{space 17}wave {c |}
survey wave 4 (2016)  {c |}{col 23}{res}{space 2}-.0598408{col 35}{space 2} .1477324{col 46}{space 1}   -0.41{col 55}{space 3}0.686{col 63}{space 4}-.3498184{col 76}{space 3} .2301368
{txt}{space 21} {c |}
{space 7}wave#c.threat4 {c |}
survey wave 4 (2016)  {c |}{col 23}{res}{space 2} .0092944{col 35}{space 2} .0504289{col 46}{space 1}    0.18{col 55}{space 3}0.854{col 63}{space 4}-.0896903{col 76}{space 3} .1082792
{txt}{space 21} {c |}
{space 15}female {c |}{col 23}{res}{space 2}-.0948897{col 35}{space 2} .0443454{col 46}{space 1}   -2.14{col 55}{space 3}0.033{col 63}{space 4}-.1819335{col 76}{space 3} -.007846
{txt}{space 18}Age {c |}{col 23}{res}{space 2} .0011872{col 35}{space 2} .0020944{col 46}{space 1}    0.57{col 55}{space 3}0.571{col 63}{space 4}-.0029239{col 76}{space 3} .0052983
{txt}{space 14}edu_age {c |}{col 23}{res}{space 2}-.0312135{col 35}{space 2} .0142429{col 46}{space 1}   -2.19{col 55}{space 3}0.029{col 63}{space 4}-.0591702{col 76}{space 3}-.0032567
{txt}{space 21} {c |}
{space 10}SocialGrade {c |}
{space 18}C1  {c |}{col 23}{res}{space 2}-.0624894{col 35}{space 2} .0535669{col 46}{space 1}   -1.17{col 55}{space 3}0.244{col 63}{space 4}-.1676336{col 76}{space 3} .0426548
{txt}{space 18}C2  {c |}{col 23}{res}{space 2} .1024679{col 35}{space 2} .0692425{col 46}{space 1}    1.48{col 55}{space 3}0.139{col 63}{space 4}-.0334454{col 76}{space 3} .2383811
{txt}{space 18}DE  {c |}{col 23}{res}{space 2}-.0650252{col 35}{space 2} .0709695{col 46}{space 1}   -0.92{col 55}{space 3}0.360{col 63}{space 4}-.2043282{col 76}{space 3} .0742778
{txt}{space 21} {c |}
{space 10}work_status {c |}
{space 3}working part time  {c |}{col 23}{res}{space 2} -.077881{col 35}{space 2} .0643158{col 46}{space 1}   -1.21{col 55}{space 3}0.226{col 63}{space 4}-.2041237{col 76}{space 3} .0483617
{txt}{space 3}full time student  {c |}{col 23}{res}{space 2}-.1477611{col 35}{space 2} .1036194{col 46}{space 1}   -1.43{col 55}{space 3}0.154{col 63}{space 4}-.3511512{col 76}{space 3} .0556291
{txt}{space 13}retired  {c |}{col 23}{res}{space 2}-.0628831{col 35}{space 2} .0712647{col 46}{space 1}   -0.88{col 55}{space 3}0.378{col 63}{space 4}-.2027656{col 76}{space 3} .0769994
{txt}{space 10}unemployed  {c |}{col 23}{res}{space 2} .3071605{col 35}{space 2}  .197312{col 46}{space 1}    1.56{col 55}{space 3}0.120{col 63}{space 4}-.0801349{col 76}{space 3} .6944558
{txt}{space 9}not working  {c |}{col 23}{res}{space 2} -.049889{col 35}{space 2} .0834026{col 46}{space 1}   -0.60{col 55}{space 3}0.550{col 63}{space 4}-.2135965{col 76}{space 3} .1138185
{txt}{space 21} {c |}
{space 15}UKborn {c |}{col 23}{res}{space 2} -.299547{col 35}{space 2} .1978278{col 46}{space 1}   -1.51{col 55}{space 3}0.130{col 63}{space 4}-.6878548{col 76}{space 3} .0887608
{txt}{space 11}authvalues {c |}{col 23}{res}{space 2} .2887706{col 35}{space 2} .0458775{col 46}{space 1}    6.29{col 55}{space 3}0.000{col 63}{space 4} .1987196{col 76}{space 3} .3788217
{txt}{space 14}selfest {c |}{col 23}{res}{space 2} .2468976{col 35}{space 2} .0869652{col 46}{space 1}    2.84{col 55}{space 3}0.005{col 63}{space 4} .0761973{col 76}{space 3} .4175978
{txt}{space 16}_cons {c |}{col 23}{res}{space 2} 1.579749{col 35}{space 2} .4191984{col 46}{space 1}    3.77{col 55}{space 3}0.000{col 63}{space 4} .7569225{col 76}{space 3} 2.402576
{txt}{hline 22}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHMus c.threat5##wave female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest 
{txt}{p}
(system variable _mi_id updated due to changed number of obs.)
{p_end}
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       817

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 779.380723
{txt}{col 1}Number of PSUs{col 19}= {res}      817
{txt}{col 49}Average RVI{col 67}= {res}    0.0000
{txt}{col 49}Largest FMI{col 67}= {res}    0.0000
{txt}{col 49}Complete DF{col 67}= {res}       816
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    814.01
{txt}{col 49}        avg{col 67}= {res}    814.01
{txt}{col 49}        max{col 67}= {res}    814.01
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  17{txt},{res}  814.0{txt}){col 67}= {res}     22.54
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}                GHMus{col 23}{c |}      Coef.{col 35}   Std. Err.{col 47}      t{col 55}   P>|t|{col 63}     [95% Con{col 76}f. Interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 14}threat5 {c |}{col 23}{res}{space 2}-.0413103{col 35}{space 2} .0734543{col 46}{space 1}   -0.56{col 55}{space 3}0.574{col 63}{space 4}-.1854925{col 76}{space 3} .1028719
{txt}{space 21} {c |}
{space 17}wave {c |}
survey wave 4 (2016)  {c |}{col 23}{res}{space 2} .1749884{col 35}{space 2} .2637734{col 46}{space 1}    0.66{col 55}{space 3}0.507{col 63}{space 4}-.3427678{col 76}{space 3} .6927446
{txt}{space 21} {c |}
{space 7}wave#c.threat5 {c |}
survey wave 4 (2016)  {c |}{col 23}{res}{space 2}-.1117221{col 35}{space 2} .0809921{col 46}{space 1}   -1.38{col 55}{space 3}0.168{col 63}{space 4}   -.2707{col 76}{space 3} .0472559
{txt}{space 21} {c |}
{space 15}female {c |}{col 23}{res}{space 2}-.0782257{col 35}{space 2} .0476381{col 46}{space 1}   -1.64{col 55}{space 3}0.101{col 63}{space 4}-.1717338{col 76}{space 3} .0152823
{txt}{space 18}Age {c |}{col 23}{res}{space 2} .0040505{col 35}{space 2} .0023291{col 46}{space 1}    1.74{col 55}{space 3}0.082{col 63}{space 4}-.0005212{col 76}{space 3} .0086222
{txt}{space 14}edu_age {c |}{col 23}{res}{space 2}-.0462271{col 35}{space 2} .0154673{col 46}{space 1}   -2.99{col 55}{space 3}0.003{col 63}{space 4}-.0765876{col 76}{space 3}-.0158665
{txt}{space 21} {c |}
{space 10}SocialGrade {c |}
{space 18}C1  {c |}{col 23}{res}{space 2} .0067765{col 35}{space 2} .0546726{col 46}{space 1}    0.12{col 55}{space 3}0.901{col 63}{space 4}-.1005394{col 76}{space 3} .1140924
{txt}{space 18}C2  {c |}{col 23}{res}{space 2} .1489714{col 35}{space 2} .0757718{col 46}{space 1}    1.97{col 55}{space 3}0.050{col 63}{space 4} .0002402{col 76}{space 3} .2977027
{txt}{space 18}DE  {c |}{col 23}{res}{space 2} .0112346{col 35}{space 2} .0754358{col 46}{space 1}    0.15{col 55}{space 3}0.882{col 63}{space 4} -.136837{col 76}{space 3} .1593062
{txt}{space 21} {c |}
{space 10}work_status {c |}
{space 3}working part time  {c |}{col 23}{res}{space 2} -.115848{col 35}{space 2} .0667408{col 46}{space 1}   -1.74{col 55}{space 3}0.083{col 63}{space 4}-.2468522{col 76}{space 3} .0151563
{txt}{space 3}full time student  {c |}{col 23}{res}{space 2}-.1981784{col 35}{space 2}  .104555{col 46}{space 1}   -1.90{col 55}{space 3}0.058{col 63}{space 4}-.4034076{col 76}{space 3} .0070509
{txt}{space 13}retired  {c |}{col 23}{res}{space 2}-.1151865{col 35}{space 2} .0782688{col 46}{space 1}   -1.47{col 55}{space 3}0.141{col 63}{space 4} -.268819{col 76}{space 3}  .038446
{txt}{space 10}unemployed  {c |}{col 23}{res}{space 2} .3711804{col 35}{space 2}  .208143{col 46}{space 1}    1.78{col 55}{space 3}0.075{col 63}{space 4}-.0373799{col 76}{space 3} .7797406
{txt}{space 9}not working  {c |}{col 23}{res}{space 2}-.0860751{col 35}{space 2} .0943819{col 46}{space 1}   -0.91{col 55}{space 3}0.362{col 63}{space 4}-.2713356{col 76}{space 3} .0991855
{txt}{space 21} {c |}
{space 15}UKborn {c |}{col 23}{res}{space 2}-.1138119{col 35}{space 2} .2700485{col 46}{space 1}   -0.42{col 55}{space 3}0.674{col 63}{space 4}-.6438853{col 76}{space 3} .4162615
{txt}{space 11}authvalues {c |}{col 23}{res}{space 2} .3650262{col 35}{space 2} .0469104{col 46}{space 1}    7.78{col 55}{space 3}0.000{col 63}{space 4} .2729466{col 76}{space 3} .4571057
{txt}{space 14}selfest {c |}{col 23}{res}{space 2} .4265789{col 35}{space 2} .0932906{col 46}{space 1}    4.57{col 55}{space 3}0.000{col 63}{space 4} .2434604{col 76}{space 3} .6096974
{txt}{space 16}_cons {c |}{col 23}{res}{space 2} 2.212276{col 35}{space 2} .5411328{col 46}{space 1}    4.09{col 55}{space 3}0.000{col 63}{space 4} 1.150095{col 76}{space 3} 3.274456
{txt}{hline 22}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. mi estimate: svy: reg GHEEur c.threat1##wave female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest
{txt}{p}
(system variable _mi_id updated due to changed number of obs.)
{p_end}
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       808

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 770.965711
{txt}{col 1}Number of PSUs{col 19}= {res}      808
{txt}{col 49}Average RVI{col 67}= {res}    0.0000
{txt}{col 49}Largest FMI{col 67}= {res}    0.0000
{txt}{col 49}Complete DF{col 67}= {res}       807
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    805.01
{txt}{col 49}        avg{col 67}= {res}    805.01
{txt}{col 49}        max{col 67}= {res}    805.01
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  17{txt},{res}  805.0{txt}){col 67}= {res}     21.50
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}               GHEEur{col 23}{c |}      Coef.{col 35}   Std. Err.{col 47}      t{col 55}   P>|t|{col 63}     [95% Con{col 76}f. Interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 14}threat1 {c |}{col 23}{res}{space 2} .0570657{col 35}{space 2} .0485576{col 46}{space 1}    1.18{col 55}{space 3}0.240{col 63}{space 4}-.0382488{col 76}{space 3} .1523801
{txt}{space 21} {c |}
{space 17}wave {c |}
survey wave 4 (2016)  {c |}{col 23}{res}{space 2}-.0753164{col 35}{space 2} .1322747{col 46}{space 1}   -0.57{col 55}{space 3}0.569{col 63}{space 4}-.3349603{col 76}{space 3} .1843276
{txt}{space 21} {c |}
{space 7}wave#c.threat1 {c |}
survey wave 4 (2016)  {c |}{col 23}{res}{space 2} .0200845{col 35}{space 2} .0572047{col 46}{space 1}    0.35{col 55}{space 3}0.726{col 63}{space 4}-.0922035{col 76}{space 3} .1323725
{txt}{space 21} {c |}
{space 15}female {c |}{col 23}{res}{space 2}-.0117235{col 35}{space 2} .0412405{col 46}{space 1}   -0.28{col 55}{space 3}0.776{col 63}{space 4}-.0926751{col 76}{space 3} .0692282
{txt}{space 18}Age {c |}{col 23}{res}{space 2}  .003619{col 35}{space 2} .0020092{col 46}{space 1}    1.80{col 55}{space 3}0.072{col 63}{space 4}-.0003248{col 76}{space 3} .0075629
{txt}{space 14}edu_age {c |}{col 23}{res}{space 2}-.0612366{col 35}{space 2} .0142267{col 46}{space 1}   -4.30{col 55}{space 3}0.000{col 63}{space 4}-.0891625{col 76}{space 3}-.0333107
{txt}{space 21} {c |}
{space 10}SocialGrade {c |}
{space 18}C1  {c |}{col 23}{res}{space 2} .0553047{col 35}{space 2} .0479109{col 46}{space 1}    1.15{col 55}{space 3}0.249{col 63}{space 4}-.0387404{col 76}{space 3} .1493497
{txt}{space 18}C2  {c |}{col 23}{res}{space 2} .1276476{col 35}{space 2} .0711441{col 46}{space 1}    1.79{col 55}{space 3}0.073{col 63}{space 4}-.0120022{col 76}{space 3} .2672974
{txt}{space 18}DE  {c |}{col 23}{res}{space 2} .1081061{col 35}{space 2} .0681573{col 46}{space 1}    1.59{col 55}{space 3}0.113{col 63}{space 4}-.0256809{col 76}{space 3} .2418931
{txt}{space 21} {c |}
{space 10}work_status {c |}
{space 3}working part time  {c |}{col 23}{res}{space 2}-.1394789{col 35}{space 2} .0578544{col 46}{space 1}   -2.41{col 55}{space 3}0.016{col 63}{space 4}-.2530422{col 76}{space 3}-.0259156
{txt}{space 3}full time student  {c |}{col 23}{res}{space 2}-.2910164{col 35}{space 2} .0814506{col 46}{space 1}   -3.57{col 55}{space 3}0.000{col 63}{space 4} -.450897{col 76}{space 3}-.1311359
{txt}{space 13}retired  {c |}{col 23}{res}{space 2}-.0020743{col 35}{space 2} .0684704{col 46}{space 1}   -0.03{col 55}{space 3}0.976{col 63}{space 4}-.1364759{col 76}{space 3} .1323272
{txt}{space 10}unemployed  {c |}{col 23}{res}{space 2} .1766559{col 35}{space 2} .2368606{col 46}{space 1}    0.75{col 55}{space 3}0.456{col 63}{space 4}-.2882815{col 76}{space 3} .6415932
{txt}{space 9}not working  {c |}{col 23}{res}{space 2}-.0711028{col 35}{space 2} .0910561{col 46}{space 1}   -0.78{col 55}{space 3}0.435{col 63}{space 4}-.2498382{col 76}{space 3} .1076326
{txt}{space 21} {c |}
{space 15}UKborn {c |}{col 23}{res}{space 2}-.4100248{col 35}{space 2} .2648328{col 46}{space 1}   -1.55{col 55}{space 3}0.122{col 63}{space 4}-.9298692{col 76}{space 3} .1098195
{txt}{space 11}authvalues {c |}{col 23}{res}{space 2} .3887328{col 35}{space 2} .0406748{col 46}{space 1}    9.56{col 55}{space 3}0.000{col 63}{space 4} .3088917{col 76}{space 3}  .468574
{txt}{space 14}selfest {c |}{col 23}{res}{space 2} .2188921{col 35}{space 2} .0818669{col 46}{space 1}    2.67{col 55}{space 3}0.008{col 63}{space 4} .0581943{col 76}{space 3} .3795899
{txt}{space 16}_cons {c |}{col 23}{res}{space 2} 2.344528{col 35}{space 2} .4438285{col 46}{space 1}    5.28{col 55}{space 3}0.000{col 63}{space 4}  1.47333{col 76}{space 3} 3.215726
{txt}{hline 22}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHEEur c.threat2##wave female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest
{txt}{p}
(system variable _mi_id updated due to changed number of obs.)
{p_end}
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       792

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 751.802999
{txt}{col 1}Number of PSUs{col 19}= {res}      792
{txt}{col 49}Average RVI{col 67}= {res}    0.0000
{txt}{col 49}Largest FMI{col 67}= {res}    0.0000
{txt}{col 49}Complete DF{col 67}= {res}       791
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    789.01
{txt}{col 49}        avg{col 67}= {res}    789.01
{txt}{col 49}        max{col 67}= {res}    789.01
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  17{txt},{res}  789.0{txt}){col 67}= {res}     22.76
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}               GHEEur{col 23}{c |}      Coef.{col 35}   Std. Err.{col 47}      t{col 55}   P>|t|{col 63}     [95% Con{col 76}f. Interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 14}threat2 {c |}{col 23}{res}{space 2} .0374181{col 35}{space 2} .0512093{col 46}{space 1}    0.73{col 55}{space 3}0.465{col 63}{space 4}-.0631046{col 76}{space 3} .1379407
{txt}{space 21} {c |}
{space 17}wave {c |}
survey wave 4 (2016)  {c |}{col 23}{res}{space 2} .2107656{col 35}{space 2} .1717828{col 46}{space 1}    1.23{col 55}{space 3}0.220{col 63}{space 4}-.1264397{col 76}{space 3} .5479709
{txt}{space 21} {c |}
{space 7}wave#c.threat2 {c |}
survey wave 4 (2016)  {c |}{col 23}{res}{space 2}-.0957417{col 35}{space 2} .0614845{col 46}{space 1}   -1.56{col 55}{space 3}0.120{col 63}{space 4}-.2164341{col 76}{space 3} .0249508
{txt}{space 21} {c |}
{space 15}female {c |}{col 23}{res}{space 2} .0102506{col 35}{space 2} .0423177{col 46}{space 1}    0.24{col 55}{space 3}0.809{col 63}{space 4} -.072818{col 76}{space 3} .0933193
{txt}{space 18}Age {c |}{col 23}{res}{space 2} .0035798{col 35}{space 2} .0020117{col 46}{space 1}    1.78{col 55}{space 3}0.076{col 63}{space 4}-.0003692{col 76}{space 3} .0075288
{txt}{space 14}edu_age {c |}{col 23}{res}{space 2} -.054209{col 35}{space 2} .0145732{col 46}{space 1}   -3.72{col 55}{space 3}0.000{col 63}{space 4}-.0828158{col 76}{space 3}-.0256021
{txt}{space 21} {c |}
{space 10}SocialGrade {c |}
{space 18}C1  {c |}{col 23}{res}{space 2} .0704052{col 35}{space 2} .0475914{col 46}{space 1}    1.48{col 55}{space 3}0.139{col 63}{space 4}-.0230156{col 76}{space 3}  .163826
{txt}{space 18}C2  {c |}{col 23}{res}{space 2} .1454316{col 35}{space 2} .0728056{col 46}{space 1}    2.00{col 55}{space 3}0.046{col 63}{space 4} .0025161{col 76}{space 3} .2883471
{txt}{space 18}DE  {c |}{col 23}{res}{space 2} .1257577{col 35}{space 2} .0685204{col 46}{space 1}    1.84{col 55}{space 3}0.067{col 63}{space 4}-.0087461{col 76}{space 3} .2602616
{txt}{space 21} {c |}
{space 10}work_status {c |}
{space 3}working part time  {c |}{col 23}{res}{space 2}-.1530311{col 35}{space 2} .0580759{col 46}{space 1}   -2.64{col 55}{space 3}0.009{col 63}{space 4}-.2670325{col 76}{space 3}-.0390296
{txt}{space 3}full time student  {c |}{col 23}{res}{space 2}-.2668844{col 35}{space 2}  .080614{col 46}{space 1}   -3.31{col 55}{space 3}0.001{col 63}{space 4}-.4251277{col 76}{space 3}-.1086411
{txt}{space 13}retired  {c |}{col 23}{res}{space 2}-.0178091{col 35}{space 2}  .070405{col 46}{space 1}   -0.25{col 55}{space 3}0.800{col 63}{space 4}-.1560123{col 76}{space 3} .1203942
{txt}{space 10}unemployed  {c |}{col 23}{res}{space 2} .2015704{col 35}{space 2} .2494321{col 46}{space 1}    0.81{col 55}{space 3}0.419{col 63}{space 4}-.2880586{col 76}{space 3} .6911994
{txt}{space 9}not working  {c |}{col 23}{res}{space 2}-.0661517{col 35}{space 2} .0929135{col 46}{space 1}   -0.71{col 55}{space 3}0.477{col 63}{space 4}-.2485385{col 76}{space 3} .1162351
{txt}{space 21} {c |}
{space 15}UKborn {c |}{col 23}{res}{space 2}-.3486934{col 35}{space 2} .3012708{col 46}{space 1}   -1.16{col 55}{space 3}0.247{col 63}{space 4}-.9400804{col 76}{space 3} .2426937
{txt}{space 11}authvalues {c |}{col 23}{res}{space 2} .4084555{col 35}{space 2} .0410159{col 46}{space 1}    9.96{col 55}{space 3}0.000{col 63}{space 4} .3279422{col 76}{space 3} .4889688
{txt}{space 14}selfest {c |}{col 23}{res}{space 2} .3050402{col 35}{space 2} .0816919{col 46}{space 1}    3.73{col 55}{space 3}0.000{col 63}{space 4}  .144681{col 76}{space 3} .4653994
{txt}{space 16}_cons {c |}{col 23}{res}{space 2} 2.103483{col 35}{space 2} .4855425{col 46}{space 1}    4.33{col 55}{space 3}0.000{col 63}{space 4} 1.150375{col 76}{space 3} 3.056591
{txt}{hline 22}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHEEur c.threat3##wave female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest
{txt}{p}
(system variable _mi_id updated due to changed number of obs.)
{p_end}
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       815

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 777.087829
{txt}{col 1}Number of PSUs{col 19}= {res}      815
{txt}{col 49}Average RVI{col 67}= {res}    0.0000
{txt}{col 49}Largest FMI{col 67}= {res}    0.0000
{txt}{col 49}Complete DF{col 67}= {res}       814
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    812.01
{txt}{col 49}        avg{col 67}= {res}    812.01
{txt}{col 49}        max{col 67}= {res}    812.01
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  17{txt},{res}  812.0{txt}){col 67}= {res}     22.44
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}               GHEEur{col 23}{c |}      Coef.{col 35}   Std. Err.{col 47}      t{col 55}   P>|t|{col 63}     [95% Con{col 76}f. Interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 14}threat3 {c |}{col 23}{res}{space 2} .0463984{col 35}{space 2} .0432328{col 46}{space 1}    1.07{col 55}{space 3}0.283{col 63}{space 4}-.0384628{col 76}{space 3} .1312596
{txt}{space 21} {c |}
{space 17}wave {c |}
survey wave 4 (2016)  {c |}{col 23}{res}{space 2}-.1294037{col 35}{space 2} .1465066{col 46}{space 1}   -0.88{col 55}{space 3}0.377{col 63}{space 4}  -.41698{col 76}{space 3} .1581727
{txt}{space 21} {c |}
{space 7}wave#c.threat3 {c |}
survey wave 4 (2016)  {c |}{col 23}{res}{space 2} .0274717{col 35}{space 2} .0532177{col 46}{space 1}    0.52{col 55}{space 3}0.606{col 63}{space 4}-.0769889{col 76}{space 3} .1319322
{txt}{space 21} {c |}
{space 15}female {c |}{col 23}{res}{space 2}-.0104449{col 35}{space 2} .0411568{col 46}{space 1}   -0.25{col 55}{space 3}0.800{col 63}{space 4} -.091231{col 76}{space 3} .0703413
{txt}{space 18}Age {c |}{col 23}{res}{space 2} .0040211{col 35}{space 2} .0019739{col 46}{space 1}    2.04{col 55}{space 3}0.042{col 63}{space 4} .0001467{col 76}{space 3} .0078956
{txt}{space 14}edu_age {c |}{col 23}{res}{space 2}-.0595265{col 35}{space 2} .0141115{col 46}{space 1}   -4.22{col 55}{space 3}0.000{col 63}{space 4}-.0872258{col 76}{space 3}-.0318272
{txt}{space 21} {c |}
{space 10}SocialGrade {c |}
{space 18}C1  {c |}{col 23}{res}{space 2} .0689053{col 35}{space 2} .0475262{col 46}{space 1}    1.45{col 55}{space 3}0.147{col 63}{space 4}-.0243833{col 76}{space 3}  .162194
{txt}{space 18}C2  {c |}{col 23}{res}{space 2} .1451652{col 35}{space 2} .0693975{col 46}{space 1}    2.09{col 55}{space 3}0.037{col 63}{space 4} .0089455{col 76}{space 3} .2813849
{txt}{space 18}DE  {c |}{col 23}{res}{space 2} .1177343{col 35}{space 2} .0676545{col 46}{space 1}    1.74{col 55}{space 3}0.082{col 63}{space 4} -.015064{col 76}{space 3} .2505326
{txt}{space 21} {c |}
{space 10}work_status {c |}
{space 3}working part time  {c |}{col 23}{res}{space 2}-.1410887{col 35}{space 2} .0573721{col 46}{space 1}   -2.46{col 55}{space 3}0.014{col 63}{space 4}-.2537038{col 76}{space 3}-.0284735
{txt}{space 3}full time student  {c |}{col 23}{res}{space 2}-.2695703{col 35}{space 2}  .079047{col 46}{space 1}   -3.41{col 55}{space 3}0.001{col 63}{space 4}-.4247308{col 76}{space 3}-.1144098
{txt}{space 13}retired  {c |}{col 23}{res}{space 2}-.0242076{col 35}{space 2} .0681904{col 46}{space 1}   -0.36{col 55}{space 3}0.723{col 63}{space 4}-.1580579{col 76}{space 3} .1096427
{txt}{space 10}unemployed  {c |}{col 23}{res}{space 2} .1852634{col 35}{space 2} .2442581{col 46}{space 1}    0.76{col 55}{space 3}0.448{col 63}{space 4}-.2941883{col 76}{space 3} .6647151
{txt}{space 9}not working  {c |}{col 23}{res}{space 2}-.0840584{col 35}{space 2} .0902564{col 46}{space 1}   -0.93{col 55}{space 3}0.352{col 63}{space 4}-.2612218{col 76}{space 3} .0931051
{txt}{space 21} {c |}
{space 15}UKborn {c |}{col 23}{res}{space 2} -.402068{col 35}{space 2} .2723473{col 46}{space 1}   -1.48{col 55}{space 3}0.140{col 63}{space 4}-.9366557{col 76}{space 3} .1325197
{txt}{space 11}authvalues {c |}{col 23}{res}{space 2} .3961491{col 35}{space 2}  .040729{col 46}{space 1}    9.73{col 55}{space 3}0.000{col 63}{space 4} .3162025{col 76}{space 3} .4760956
{txt}{space 14}selfest {c |}{col 23}{res}{space 2} .2378468{col 35}{space 2} .0786642{col 46}{space 1}    3.02{col 55}{space 3}0.003{col 63}{space 4} .0834376{col 76}{space 3} .3922561
{txt}{space 16}_cons {c |}{col 23}{res}{space 2} 2.273964{col 35}{space 2} .4504182{col 46}{space 1}    5.05{col 55}{space 3}0.000{col 63}{space 4} 1.389843{col 76}{space 3} 3.158086
{txt}{hline 22}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHEEur c.threat4##wave female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest
{txt}{p}
(system variable _mi_id updated due to changed number of obs.)
{p_end}
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       809

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 772.088032
{txt}{col 1}Number of PSUs{col 19}= {res}      809
{txt}{col 49}Average RVI{col 67}= {res}    0.0000
{txt}{col 49}Largest FMI{col 67}= {res}    0.0000
{txt}{col 49}Complete DF{col 67}= {res}       808
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    806.01
{txt}{col 49}        avg{col 67}= {res}    806.01
{txt}{col 49}        max{col 67}= {res}    806.01
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  17{txt},{res}  806.0{txt}){col 67}= {res}     36.79
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}               GHEEur{col 23}{c |}      Coef.{col 35}   Std. Err.{col 47}      t{col 55}   P>|t|{col 63}     [95% Con{col 76}f. Interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 14}threat4 {c |}{col 23}{res}{space 2} .1831396{col 35}{space 2} .0357174{col 46}{space 1}    5.13{col 55}{space 3}0.000{col 63}{space 4} .1130296{col 76}{space 3} .2532496
{txt}{space 21} {c |}
{space 17}wave {c |}
survey wave 4 (2016)  {c |}{col 23}{res}{space 2}-.1473282{col 35}{space 2} .1221864{col 46}{space 1}   -1.21{col 55}{space 3}0.228{col 63}{space 4}-.3871693{col 76}{space 3} .0925128
{txt}{space 21} {c |}
{space 7}wave#c.threat4 {c |}
survey wave 4 (2016)  {c |}{col 23}{res}{space 2} .0535857{col 35}{space 2}  .041894{col 46}{space 1}    1.28{col 55}{space 3}0.201{col 63}{space 4}-.0286486{col 76}{space 3}   .13582
{txt}{space 21} {c |}
{space 15}female {c |}{col 23}{res}{space 2}-.0107073{col 35}{space 2} .0386459{col 46}{space 1}   -0.28{col 55}{space 3}0.782{col 63}{space 4}-.0865657{col 76}{space 3} .0651512
{txt}{space 18}Age {c |}{col 23}{res}{space 2} .0010965{col 35}{space 2} .0019318{col 46}{space 1}    0.57{col 55}{space 3}0.570{col 63}{space 4}-.0026956{col 76}{space 3} .0048885
{txt}{space 14}edu_age {c |}{col 23}{res}{space 2}-.0429417{col 35}{space 2} .0134864{col 46}{space 1}   -3.18{col 55}{space 3}0.002{col 63}{space 4}-.0694144{col 76}{space 3} -.016469
{txt}{space 21} {c |}
{space 10}SocialGrade {c |}
{space 18}C1  {c |}{col 23}{res}{space 2} .0155505{col 35}{space 2} .0453625{col 46}{space 1}    0.34{col 55}{space 3}0.732{col 63}{space 4}-.0734921{col 76}{space 3} .1045931
{txt}{space 18}C2  {c |}{col 23}{res}{space 2} .0754773{col 35}{space 2} .0669914{col 46}{space 1}    1.13{col 55}{space 3}0.260{col 63}{space 4}-.0560209{col 76}{space 3} .2069755
{txt}{space 18}DE  {c |}{col 23}{res}{space 2} .0754942{col 35}{space 2}  .064336{col 46}{space 1}    1.17{col 55}{space 3}0.241{col 63}{space 4}-.0507916{col 76}{space 3}   .20178
{txt}{space 21} {c |}
{space 10}work_status {c |}
{space 3}working part time  {c |}{col 23}{res}{space 2}-.1460048{col 35}{space 2}  .056129{col 46}{space 1}   -2.60{col 55}{space 3}0.009{col 63}{space 4}-.2561811{col 76}{space 3}-.0358286
{txt}{space 3}full time student  {c |}{col 23}{res}{space 2}  -.22458{col 35}{space 2} .0778776{col 46}{space 1}   -2.88{col 55}{space 3}0.004{col 63}{space 4}-.3774469{col 76}{space 3}-.0717131
{txt}{space 13}retired  {c |}{col 23}{res}{space 2} .0145433{col 35}{space 2} .0641732{col 46}{space 1}    0.23{col 55}{space 3}0.821{col 63}{space 4} -.111423{col 76}{space 3} .1405095
{txt}{space 10}unemployed  {c |}{col 23}{res}{space 2} .1691199{col 35}{space 2}  .223726{col 46}{space 1}    0.76{col 55}{space 3}0.450{col 63}{space 4}-.2700344{col 76}{space 3} .6082743
{txt}{space 9}not working  {c |}{col 23}{res}{space 2}-.0718384{col 35}{space 2} .0802201{col 46}{space 1}   -0.90{col 55}{space 3}0.371{col 63}{space 4}-.2293032{col 76}{space 3} .0856265
{txt}{space 21} {c |}
{space 15}UKborn {c |}{col 23}{res}{space 2}-.4624148{col 35}{space 2} .2026303{col 46}{space 1}   -2.28{col 55}{space 3}0.023{col 63}{space 4}-.8601602{col 76}{space 3}-.0646693
{txt}{space 11}authvalues {c |}{col 23}{res}{space 2} .3182195{col 35}{space 2} .0400811{col 46}{space 1}    7.94{col 55}{space 3}0.000{col 63}{space 4} .2395439{col 76}{space 3} .3968952
{txt}{space 14}selfest {c |}{col 23}{res}{space 2} .1951681{col 35}{space 2} .0739875{col 46}{space 1}    2.64{col 55}{space 3}0.009{col 63}{space 4} .0499373{col 76}{space 3}  .340399
{txt}{space 16}_cons {c |}{col 23}{res}{space 2} 1.965721{col 35}{space 2} .3866148{col 46}{space 1}    5.08{col 55}{space 3}0.000{col 63}{space 4} 1.206831{col 76}{space 3} 2.724612
{txt}{hline 22}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHEEur c.threat5##wave female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest
{txt}{p}
(system variable _mi_id updated due to changed number of obs.)
{p_end}
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       806

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 766.511132
{txt}{col 1}Number of PSUs{col 19}= {res}      806
{txt}{col 49}Average RVI{col 67}= {res}    0.0000
{txt}{col 49}Largest FMI{col 67}= {res}    0.0000
{txt}{col 49}Complete DF{col 67}= {res}       805
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    803.01
{txt}{col 49}        avg{col 67}= {res}    803.01
{txt}{col 49}        max{col 67}= {res}    803.01
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  17{txt},{res}  803.0{txt}){col 67}= {res}     25.93
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}               GHEEur{col 23}{c |}      Coef.{col 35}   Std. Err.{col 47}      t{col 55}   P>|t|{col 63}     [95% Con{col 76}f. Interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 14}threat5 {c |}{col 23}{res}{space 2} .0026007{col 35}{space 2} .0530374{col 46}{space 1}    0.05{col 55}{space 3}0.961{col 63}{space 4}-.1015077{col 76}{space 3}  .106709
{txt}{space 21} {c |}
{space 17}wave {c |}
survey wave 4 (2016)  {c |}{col 23}{res}{space 2} .3796324{col 35}{space 2} .1875317{col 46}{space 1}    2.02{col 55}{space 3}0.043{col 63}{space 4} .0115222{col 76}{space 3} .7477426
{txt}{space 21} {c |}
{space 7}wave#c.threat5 {c |}
survey wave 4 (2016)  {c |}{col 23}{res}{space 2}-.1630805{col 35}{space 2} .0634198{col 46}{space 1}   -2.57{col 55}{space 3}0.010{col 63}{space 4}-.2875687{col 76}{space 3}-.0385924
{txt}{space 21} {c |}
{space 15}female {c |}{col 23}{res}{space 2} .0145794{col 35}{space 2}  .040999{col 46}{space 1}    0.36{col 55}{space 3}0.722{col 63}{space 4}-.0658984{col 76}{space 3} .0950572
{txt}{space 18}Age {c |}{col 23}{res}{space 2} .0027037{col 35}{space 2} .0019501{col 46}{space 1}    1.39{col 55}{space 3}0.166{col 63}{space 4}-.0011242{col 76}{space 3} .0065316
{txt}{space 14}edu_age {c |}{col 23}{res}{space 2}-.0566736{col 35}{space 2} .0145496{col 46}{space 1}   -3.90{col 55}{space 3}0.000{col 63}{space 4}-.0852334{col 76}{space 3}-.0281138
{txt}{space 21} {c |}
{space 10}SocialGrade {c |}
{space 18}C1  {c |}{col 23}{res}{space 2} .0784592{col 35}{space 2} .0460716{col 46}{space 1}    1.70{col 55}{space 3}0.089{col 63}{space 4}-.0119758{col 76}{space 3} .1688943
{txt}{space 18}C2  {c |}{col 23}{res}{space 2} .1170324{col 35}{space 2} .0701098{col 46}{space 1}    1.67{col 55}{space 3}0.095{col 63}{space 4}-.0205877{col 76}{space 3} .2546526
{txt}{space 18}DE  {c |}{col 23}{res}{space 2} .1049117{col 35}{space 2}   .06523{col 46}{space 1}    1.61{col 55}{space 3}0.108{col 63}{space 4}-.0231298{col 76}{space 3} .2329531
{txt}{space 21} {c |}
{space 10}work_status {c |}
{space 3}working part time  {c |}{col 23}{res}{space 2}-.1571621{col 35}{space 2} .0553111{col 46}{space 1}   -2.84{col 55}{space 3}0.005{col 63}{space 4}-.2657336{col 76}{space 3}-.0485907
{txt}{space 3}full time student  {c |}{col 23}{res}{space 2}-.2655494{col 35}{space 2} .0790542{col 46}{space 1}   -3.36{col 55}{space 3}0.001{col 63}{space 4}-.4207266{col 76}{space 3}-.1103722
{txt}{space 13}retired  {c |}{col 23}{res}{space 2}-.0083032{col 35}{space 2} .0667249{col 46}{space 1}   -0.12{col 55}{space 3}0.901{col 63}{space 4} -.139279{col 76}{space 3} .1226725
{txt}{space 10}unemployed  {c |}{col 23}{res}{space 2} .1588171{col 35}{space 2} .2248405{col 46}{space 1}    0.71{col 55}{space 3}0.480{col 63}{space 4}-.2825273{col 76}{space 3} .6001616
{txt}{space 9}not working  {c |}{col 23}{res}{space 2}-.1072943{col 35}{space 2} .0942091{col 46}{space 1}   -1.14{col 55}{space 3}0.255{col 63}{space 4}-.2922193{col 76}{space 3} .0776308
{txt}{space 21} {c |}
{space 15}UKborn {c |}{col 23}{res}{space 2}-.3884739{col 35}{space 2} .2529803{col 46}{space 1}   -1.54{col 55}{space 3}0.125{col 63}{space 4}-.8850546{col 76}{space 3} .1081067
{txt}{space 11}authvalues {c |}{col 23}{res}{space 2} .3630263{col 35}{space 2} .0410263{col 46}{space 1}    8.85{col 55}{space 3}0.000{col 63}{space 4} .2824949{col 76}{space 3} .4435578
{txt}{space 14}selfest {c |}{col 23}{res}{space 2} .2952392{col 35}{space 2} .0785735{col 46}{space 1}    3.76{col 55}{space 3}0.000{col 63}{space 4} .1410054{col 76}{space 3} .4494729
{txt}{space 16}_cons {c |}{col 23}{res}{space 2} 2.441001{col 35}{space 2}  .451455{col 46}{space 1}    5.41{col 55}{space 3}0.000{col 63}{space 4}  1.55483{col 76}{space 3} 3.327172
{txt}{hline 22}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. mi estimate: svy: reg GHwhite c.threat1##wave female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest
{txt}{p}
(system variable _mi_id updated due to changed number of obs.)
{p_end}
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       775

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 740.515353
{txt}{col 1}Number of PSUs{col 19}= {res}      775
{txt}{col 49}Average RVI{col 67}= {res}    0.0000
{txt}{col 49}Largest FMI{col 67}= {res}    0.0000
{txt}{col 49}Complete DF{col 67}= {res}       774
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    772.01
{txt}{col 49}        avg{col 67}= {res}    772.01
{txt}{col 49}        max{col 67}= {res}    772.01
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  17{txt},{res}  772.0{txt}){col 67}= {res}      4.29
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}              GHwhite{col 23}{c |}      Coef.{col 35}   Std. Err.{col 47}      t{col 55}   P>|t|{col 63}     [95% Con{col 76}f. Interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 14}threat1 {c |}{col 23}{res}{space 2} .2086853{col 35}{space 2} .1792824{col 46}{space 1}    1.16{col 55}{space 3}0.245{col 63}{space 4}-.1432534{col 76}{space 3} .5606241
{txt}{space 21} {c |}
{space 17}wave {c |}
survey wave 4 (2016)  {c |}{col 23}{res}{space 2}-.3106146{col 35}{space 2} .4842426{col 46}{space 1}   -0.64{col 55}{space 3}0.521{col 63}{space 4}-1.261203{col 76}{space 3} .6399737
{txt}{space 21} {c |}
{space 7}wave#c.threat1 {c |}
survey wave 4 (2016)  {c |}{col 23}{res}{space 2}-.0970549{col 35}{space 2} .1824619{col 46}{space 1}   -0.53{col 55}{space 3}0.595{col 63}{space 4}-.4552351{col 76}{space 3} .2611253
{txt}{space 21} {c |}
{space 15}female {c |}{col 23}{res}{space 2} .0716099{col 35}{space 2} .0620465{col 46}{space 1}    1.15{col 55}{space 3}0.249{col 63}{space 4}  -.05019{col 76}{space 3} .1934098
{txt}{space 18}Age {c |}{col 23}{res}{space 2}-.0071368{col 35}{space 2} .0034994{col 46}{space 1}   -2.04{col 55}{space 3}0.042{col 63}{space 4}-.0140063{col 76}{space 3}-.0002673
{txt}{space 14}edu_age {c |}{col 23}{res}{space 2} -.017783{col 35}{space 2} .0216509{col 46}{space 1}   -0.82{col 55}{space 3}0.412{col 63}{space 4}-.0602846{col 76}{space 3} .0247186
{txt}{space 21} {c |}
{space 10}SocialGrade {c |}
{space 18}C1  {c |}{col 23}{res}{space 2}   .07466{col 35}{space 2} .0710858{col 46}{space 1}    1.05{col 55}{space 3}0.294{col 63}{space 4}-.0648844{col 76}{space 3} .2142045
{txt}{space 18}C2  {c |}{col 23}{res}{space 2} .2409852{col 35}{space 2} .1096087{col 46}{space 1}    2.20{col 55}{space 3}0.028{col 63}{space 4} .0258188{col 76}{space 3} .4561516
{txt}{space 18}DE  {c |}{col 23}{res}{space 2} .1910022{col 35}{space 2} .1045112{col 46}{space 1}    1.83{col 55}{space 3}0.068{col 63}{space 4}-.0141577{col 76}{space 3} .3961621
{txt}{space 21} {c |}
{space 10}work_status {c |}
{space 3}working part time  {c |}{col 23}{res}{space 2} .0255737{col 35}{space 2} .1175068{col 46}{space 1}    0.22{col 55}{space 3}0.828{col 63}{space 4}-.2050971{col 76}{space 3} .2562445
{txt}{space 3}full time student  {c |}{col 23}{res}{space 2}-.1592523{col 35}{space 2} .1259661{col 46}{space 1}   -1.26{col 55}{space 3}0.207{col 63}{space 4}-.4065291{col 76}{space 3} .0880245
{txt}{space 13}retired  {c |}{col 23}{res}{space 2} .1495852{col 35}{space 2}  .098286{col 46}{space 1}    1.52{col 55}{space 3}0.128{col 63}{space 4}-.0433542{col 76}{space 3} .3425246
{txt}{space 10}unemployed  {c |}{col 23}{res}{space 2}-.4494889{col 35}{space 2} .2303908{col 46}{space 1}   -1.95{col 55}{space 3}0.051{col 63}{space 4}-.9017556{col 76}{space 3} .0027778
{txt}{space 9}not working  {c |}{col 23}{res}{space 2} .1723203{col 35}{space 2} .1607306{col 46}{space 1}    1.07{col 55}{space 3}0.284{col 63}{space 4}-.1432005{col 76}{space 3}  .487841
{txt}{space 21} {c |}
{space 15}UKborn {c |}{col 23}{res}{space 2}  .252709{col 35}{space 2} .2435288{col 46}{space 1}    1.04{col 55}{space 3}0.300{col 63}{space 4}-.2253482{col 76}{space 3} .7307662
{txt}{space 11}authvalues {c |}{col 23}{res}{space 2} .1420706{col 35}{space 2} .0641335{col 46}{space 1}    2.22{col 55}{space 3}0.027{col 63}{space 4} .0161738{col 76}{space 3} .2679674
{txt}{space 14}selfest {c |}{col 23}{res}{space 2}-.0128707{col 35}{space 2} .1417255{col 46}{space 1}   -0.09{col 55}{space 3}0.928{col 63}{space 4}-.2910837{col 76}{space 3} .2653424
{txt}{space 16}_cons {c |}{col 23}{res}{space 2} 2.064737{col 35}{space 2} .8366146{col 46}{space 1}    2.47{col 55}{space 3}0.014{col 63}{space 4}  .422428{col 76}{space 3} 3.707047
{txt}{hline 22}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHwhite c.threat2##wave female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest
{txt}{p}
(system variable _mi_id updated due to changed number of obs.)
{p_end}
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       758

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 719.368408
{txt}{col 1}Number of PSUs{col 19}= {res}      758
{txt}{col 49}Average RVI{col 67}= {res}    0.0000
{txt}{col 49}Largest FMI{col 67}= {res}    0.0000
{txt}{col 49}Complete DF{col 67}= {res}       757
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    755.01
{txt}{col 49}        avg{col 67}= {res}    755.01
{txt}{col 49}        max{col 67}= {res}    755.01
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  17{txt},{res}  755.0{txt}){col 67}= {res}      3.43
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}              GHwhite{col 23}{c |}      Coef.{col 35}   Std. Err.{col 47}      t{col 55}   P>|t|{col 63}     [95% Con{col 76}f. Interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 14}threat2 {c |}{col 23}{res}{space 2} .0165454{col 35}{space 2} .1610175{col 46}{space 1}    0.10{col 55}{space 3}0.918{col 63}{space 4}-.2995498{col 76}{space 3} .3326406
{txt}{space 21} {c |}
{space 17}wave {c |}
survey wave 4 (2016)  {c |}{col 23}{res}{space 2} -.678926{col 35}{space 2} .4983421{col 46}{space 1}   -1.36{col 55}{space 3}0.173{col 63}{space 4}-1.657227{col 76}{space 3} .2993747
{txt}{space 21} {c |}
{space 7}wave#c.threat2 {c |}
survey wave 4 (2016)  {c |}{col 23}{res}{space 2} .0658349{col 35}{space 2} .1633291{col 46}{space 1}    0.40{col 55}{space 3}0.687{col 63}{space 4}-.2547981{col 76}{space 3}  .386468
{txt}{space 21} {c |}
{space 15}female {c |}{col 23}{res}{space 2} .0600832{col 35}{space 2} .0608633{col 46}{space 1}    0.99{col 55}{space 3}0.324{col 63}{space 4}-.0593981{col 76}{space 3} .1795646
{txt}{space 18}Age {c |}{col 23}{res}{space 2}-.0038726{col 35}{space 2} .0027683{col 46}{space 1}   -1.40{col 55}{space 3}0.162{col 63}{space 4} -.009307{col 76}{space 3} .0015618
{txt}{space 14}edu_age {c |}{col 23}{res}{space 2}-.0023439{col 35}{space 2}  .018829{col 46}{space 1}   -0.12{col 55}{space 3}0.901{col 63}{space 4}-.0393072{col 76}{space 3} .0346194
{txt}{space 21} {c |}
{space 10}SocialGrade {c |}
{space 18}C1  {c |}{col 23}{res}{space 2} .0858025{col 35}{space 2} .0718305{col 46}{space 1}    1.19{col 55}{space 3}0.233{col 63}{space 4}-.0552088{col 76}{space 3} .2268137
{txt}{space 18}C2  {c |}{col 23}{res}{space 2} .1861094{col 35}{space 2} .0988026{col 46}{space 1}    1.88{col 55}{space 3}0.060{col 63}{space 4} -.007851{col 76}{space 3} .3800699
{txt}{space 18}DE  {c |}{col 23}{res}{space 2}   .17455{col 35}{space 2}  .106424{col 46}{space 1}    1.64{col 55}{space 3}0.101{col 63}{space 4}-.0343722{col 76}{space 3} .3834722
{txt}{space 21} {c |}
{space 10}work_status {c |}
{space 3}working part time  {c |}{col 23}{res}{space 2}-.0754519{col 35}{space 2} .0785095{col 46}{space 1}   -0.96{col 55}{space 3}0.337{col 63}{space 4}-.2295748{col 76}{space 3}  .078671
{txt}{space 3}full time student  {c |}{col 23}{res}{space 2}-.1355337{col 35}{space 2} .1265858{col 46}{space 1}   -1.07{col 55}{space 3}0.285{col 63}{space 4}-.3840356{col 76}{space 3} .1129682
{txt}{space 13}retired  {c |}{col 23}{res}{space 2} .0841878{col 35}{space 2} .0904416{col 46}{space 1}    0.93{col 55}{space 3}0.352{col 63}{space 4}-.0933591{col 76}{space 3} .2617347
{txt}{space 10}unemployed  {c |}{col 23}{res}{space 2}-.4414915{col 35}{space 2} .2148214{col 46}{space 1}   -2.06{col 55}{space 3}0.040{col 63}{space 4}-.8632097{col 76}{space 3}-.0197733
{txt}{space 9}not working  {c |}{col 23}{res}{space 2} .2208939{col 35}{space 2} .1686563{col 46}{space 1}    1.31{col 55}{space 3}0.191{col 63}{space 4}-.1101973{col 76}{space 3}  .551985
{txt}{space 21} {c |}
{space 15}UKborn {c |}{col 23}{res}{space 2} .4178106{col 35}{space 2} .2859059{col 46}{space 1}    1.46{col 55}{space 3}0.144{col 63}{space 4}-.1434544{col 76}{space 3} .9790756
{txt}{space 11}authvalues {c |}{col 23}{res}{space 2} .1973264{col 35}{space 2} .0655466{col 46}{space 1}    3.01{col 55}{space 3}0.003{col 63}{space 4} .0686511{col 76}{space 3} .3260017
{txt}{space 14}selfest {c |}{col 23}{res}{space 2} .1075873{col 35}{space 2} .1198958{col 46}{space 1}    0.90{col 55}{space 3}0.370{col 63}{space 4}-.1277814{col 76}{space 3}  .342956
{txt}{space 16}_cons {c |}{col 23}{res}{space 2} 1.737243{col 35}{space 2} .7346043{col 46}{space 1}    2.36{col 55}{space 3}0.018{col 63}{space 4} .2951331{col 76}{space 3} 3.179353
{txt}{hline 22}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHwhite c.threat3##wave female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest
{txt}{p}
(system variable _mi_id updated due to changed number of obs.)
{p_end}
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       779

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 742.357899
{txt}{col 1}Number of PSUs{col 19}= {res}      779
{txt}{col 49}Average RVI{col 67}= {res}    0.0000
{txt}{col 49}Largest FMI{col 67}= {res}    0.0000
{txt}{col 49}Complete DF{col 67}= {res}       778
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    776.01
{txt}{col 49}        avg{col 67}= {res}    776.01
{txt}{col 49}        max{col 67}= {res}    776.01
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  17{txt},{res}  776.0{txt}){col 67}= {res}      4.04
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}              GHwhite{col 23}{c |}      Coef.{col 35}   Std. Err.{col 47}      t{col 55}   P>|t|{col 63}     [95% Con{col 76}f. Interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 14}threat3 {c |}{col 23}{res}{space 2} .3270541{col 35}{space 2} .1556571{col 46}{space 1}    2.10{col 55}{space 3}0.036{col 63}{space 4} .0214951{col 76}{space 3}  .632613
{txt}{space 21} {c |}
{space 17}wave {c |}
survey wave 4 (2016)  {c |}{col 23}{res}{space 2} .1969131{col 35}{space 2} .4706511{col 46}{space 1}    0.42{col 55}{space 3}0.676{col 63}{space 4} -.726987{col 76}{space 3} 1.120813
{txt}{space 21} {c |}
{space 7}wave#c.threat3 {c |}
survey wave 4 (2016)  {c |}{col 23}{res}{space 2} -.233227{col 35}{space 2} .1581888{col 46}{space 1}   -1.47{col 55}{space 3}0.141{col 63}{space 4}-.5437557{col 76}{space 3} .0773017
{txt}{space 21} {c |}
{space 15}female {c |}{col 23}{res}{space 2} .0293413{col 35}{space 2} .0595938{col 46}{space 1}    0.49{col 55}{space 3}0.623{col 63}{space 4}-.0876428{col 76}{space 3} .1463254
{txt}{space 18}Age {c |}{col 23}{res}{space 2}-.0044553{col 35}{space 2}  .002855{col 46}{space 1}   -1.56{col 55}{space 3}0.119{col 63}{space 4}-.0100597{col 76}{space 3} .0011491
{txt}{space 14}edu_age {c |}{col 23}{res}{space 2}-.0059272{col 35}{space 2} .0179084{col 46}{space 1}   -0.33{col 55}{space 3}0.741{col 63}{space 4}-.0410819{col 76}{space 3} .0292274
{txt}{space 21} {c |}
{space 10}SocialGrade {c |}
{space 18}C1  {c |}{col 23}{res}{space 2} .0734778{col 35}{space 2} .0695902{col 46}{space 1}    1.06{col 55}{space 3}0.291{col 63}{space 4}-.0631294{col 76}{space 3} .2100851
{txt}{space 18}C2  {c |}{col 23}{res}{space 2} .1441414{col 35}{space 2} .0882727{col 46}{space 1}    1.63{col 55}{space 3}0.103{col 63}{space 4}-.0291402{col 76}{space 3}  .317423
{txt}{space 18}DE  {c |}{col 23}{res}{space 2} .1851503{col 35}{space 2} .1046696{col 46}{space 1}    1.77{col 55}{space 3}0.077{col 63}{space 4}-.0203188{col 76}{space 3} .3906194
{txt}{space 21} {c |}
{space 10}work_status {c |}
{space 3}working part time  {c |}{col 23}{res}{space 2}-.0626755{col 35}{space 2} .0763868{col 46}{space 1}   -0.82{col 55}{space 3}0.412{col 63}{space 4}-.2126247{col 76}{space 3} .0872737
{txt}{space 3}full time student  {c |}{col 23}{res}{space 2}-.1131255{col 35}{space 2} .1264534{col 46}{space 1}   -0.89{col 55}{space 3}0.371{col 63}{space 4}-.3613568{col 76}{space 3} .1351057
{txt}{space 13}retired  {c |}{col 23}{res}{space 2} .0899664{col 35}{space 2} .0903881{col 46}{space 1}    1.00{col 55}{space 3}0.320{col 63}{space 4}-.0874677{col 76}{space 3} .2674005
{txt}{space 10}unemployed  {c |}{col 23}{res}{space 2}-.3768003{col 35}{space 2} .2447958{col 46}{space 1}   -1.54{col 55}{space 3}0.124{col 63}{space 4}-.8573407{col 76}{space 3} .1037401
{txt}{space 9}not working  {c |}{col 23}{res}{space 2} .1738991{col 35}{space 2}  .159225{col 46}{space 1}    1.09{col 55}{space 3}0.275{col 63}{space 4}-.1386636{col 76}{space 3} .4864618
{txt}{space 21} {c |}
{space 15}UKborn {c |}{col 23}{res}{space 2} .3349217{col 35}{space 2} .2492701{col 46}{space 1}    1.34{col 55}{space 3}0.179{col 63}{space 4} -.154402{col 76}{space 3} .8242453
{txt}{space 11}authvalues {c |}{col 23}{res}{space 2} .1709343{col 35}{space 2} .0640836{col 46}{space 1}    2.67{col 55}{space 3}0.008{col 63}{space 4} .0451366{col 76}{space 3}  .296732
{txt}{space 14}selfest {c |}{col 23}{res}{space 2} .0727173{col 35}{space 2} .1153622{col 46}{space 1}    0.63{col 55}{space 3}0.529{col 63}{space 4}-.1537417{col 76}{space 3} .2991762
{txt}{space 16}_cons {c |}{col 23}{res}{space 2} 1.088332{col 35}{space 2} .6863747{col 46}{space 1}    1.59{col 55}{space 3}0.113{col 63}{space 4}-.2590392{col 76}{space 3} 2.435703
{txt}{hline 22}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHwhite c.threat4##wave female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest
{txt}{p}
(system variable _mi_id updated due to changed number of obs.)
{p_end}
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       774

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 738.062864
{txt}{col 1}Number of PSUs{col 19}= {res}      774
{txt}{col 49}Average RVI{col 67}= {res}    0.0000
{txt}{col 49}Largest FMI{col 67}= {res}    0.0000
{txt}{col 49}Complete DF{col 67}= {res}       773
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    771.01
{txt}{col 49}        avg{col 67}= {res}    771.01
{txt}{col 49}        max{col 67}= {res}    771.01
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  17{txt},{res}  771.0{txt}){col 67}= {res}      3.88
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}              GHwhite{col 23}{c |}      Coef.{col 35}   Std. Err.{col 47}      t{col 55}   P>|t|{col 63}     [95% Con{col 76}f. Interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 14}threat4 {c |}{col 23}{res}{space 2}-.0135749{col 35}{space 2} .1567249{col 46}{space 1}   -0.09{col 55}{space 3}0.931{col 63}{space 4} -.321233{col 76}{space 3} .2940832
{txt}{space 21} {c |}
{space 17}wave {c |}
survey wave 4 (2016)  {c |}{col 23}{res}{space 2}-.7088712{col 35}{space 2} .5265597{col 46}{space 1}   -1.35{col 55}{space 3}0.179{col 63}{space 4}-1.742532{col 76}{space 3} .3247895
{txt}{space 21} {c |}
{space 7}wave#c.threat4 {c |}
survey wave 4 (2016)  {c |}{col 23}{res}{space 2} .0759389{col 35}{space 2} .1598165{col 46}{space 1}    0.48{col 55}{space 3}0.635{col 63}{space 4}-.2377881{col 76}{space 3}  .389666
{txt}{space 21} {c |}
{space 15}female {c |}{col 23}{res}{space 2} .0539906{col 35}{space 2} .0597843{col 46}{space 1}    0.90{col 55}{space 3}0.367{col 63}{space 4}-.0633687{col 76}{space 3}   .17135
{txt}{space 18}Age {c |}{col 23}{res}{space 2}-.0051652{col 35}{space 2} .0029064{col 46}{space 1}   -1.78{col 55}{space 3}0.076{col 63}{space 4}-.0108705{col 76}{space 3} .0005401
{txt}{space 14}edu_age {c |}{col 23}{res}{space 2}-.0073804{col 35}{space 2} .0184618{col 46}{space 1}   -0.40{col 55}{space 3}0.689{col 63}{space 4}-.0436218{col 76}{space 3} .0288611
{txt}{space 21} {c |}
{space 10}SocialGrade {c |}
{space 18}C1  {c |}{col 23}{res}{space 2} .0709176{col 35}{space 2} .0709334{col 46}{space 1}    1.00{col 55}{space 3}0.318{col 63}{space 4}-.0683279{col 76}{space 3} .2101631
{txt}{space 18}C2  {c |}{col 23}{res}{space 2} .1497598{col 35}{space 2} .0902828{col 46}{space 1}    1.66{col 55}{space 3}0.098{col 63}{space 4}-.0274695{col 76}{space 3}  .326989
{txt}{space 18}DE  {c |}{col 23}{res}{space 2} .1841705{col 35}{space 2} .1041998{col 46}{space 1}    1.77{col 55}{space 3}0.078{col 63}{space 4}-.0203784{col 76}{space 3} .3887194
{txt}{space 21} {c |}
{space 10}work_status {c |}
{space 3}working part time  {c |}{col 23}{res}{space 2}-.0723766{col 35}{space 2} .0784161{col 46}{space 1}   -0.92{col 55}{space 3}0.356{col 63}{space 4}-.2263109{col 76}{space 3} .0815577
{txt}{space 3}full time student  {c |}{col 23}{res}{space 2}-.1170237{col 35}{space 2} .1236646{col 46}{space 1}   -0.95{col 55}{space 3}0.344{col 63}{space 4}-.3597829{col 76}{space 3} .1257355
{txt}{space 13}retired  {c |}{col 23}{res}{space 2} .0826502{col 35}{space 2} .0869439{col 46}{space 1}    0.95{col 55}{space 3}0.342{col 63}{space 4}-.0880246{col 76}{space 3}  .253325
{txt}{space 10}unemployed  {c |}{col 23}{res}{space 2}-.4659578{col 35}{space 2} .2233516{col 46}{space 1}   -2.09{col 55}{space 3}0.037{col 63}{space 4}-.9044072{col 76}{space 3}-.0275084
{txt}{space 9}not working  {c |}{col 23}{res}{space 2} .1569591{col 35}{space 2} .1591303{col 46}{space 1}    0.99{col 55}{space 3}0.324{col 63}{space 4} -.155421{col 76}{space 3} .4693391
{txt}{space 21} {c |}
{space 15}UKborn {c |}{col 23}{res}{space 2} .2486732{col 35}{space 2} .2658875{col 46}{space 1}    0.94{col 55}{space 3}0.350{col 63}{space 4}-.2732761{col 76}{space 3} .7706224
{txt}{space 11}authvalues {c |}{col 23}{res}{space 2} .1640719{col 35}{space 2} .0676508{col 46}{space 1}    2.43{col 55}{space 3}0.016{col 63}{space 4} .0312704{col 76}{space 3} .2968735
{txt}{space 14}selfest {c |}{col 23}{res}{space 2}  .084686{col 35}{space 2} .1179619{col 46}{space 1}    0.72{col 55}{space 3}0.473{col 63}{space 4}-.1468786{col 76}{space 3} .3162505
{txt}{space 16}_cons {c |}{col 23}{res}{space 2} 2.229487{col 35}{space 2} .6451786{col 46}{space 1}    3.46{col 55}{space 3}0.001{col 63}{space 4} .9629721{col 76}{space 3} 3.496002
{txt}{hline 22}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. mi estimate: svy: reg GHwhite c.threat5##wave female Age edu_age i.SocialGrade i.work_status UKborn authvalues selfest
{txt}{p}
(system variable _mi_id updated due to changed number of obs.)
{p_end}
{res}
{txt}Multiple-imputation estimates{col 49}Imputations{col 67}= {res}        10
{txt}Survey: Linear regression{col 49}Number of obs{col 67}= {res}       764

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 49}Population size{col 67}={res} 727.330667
{txt}{col 1}Number of PSUs{col 19}= {res}      764
{txt}{col 49}Average RVI{col 67}= {res}    0.0000
{txt}{col 49}Largest FMI{col 67}= {res}    0.0000
{txt}{col 49}Complete DF{col 67}= {res}       763
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 49}DF:     min{col 67}= {res}    761.01
{txt}{col 49}        avg{col 67}= {res}    761.01
{txt}{col 49}        max{col 67}= {res}    761.01
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 49}F({res}  17{txt},{res}  761.0{txt}){col 67}= {res}      3.21
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 49}Prob > F{col 67}= {res}    0.0000

{txt}{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}              GHwhite{col 23}{c |}      Coef.{col 35}   Std. Err.{col 47}      t{col 55}   P>|t|{col 63}     [95% Con{col 76}f. Interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 14}threat5 {c |}{col 23}{res}{space 2} .0522092{col 35}{space 2} .1623514{col 46}{space 1}    0.32{col 55}{space 3}0.748{col 63}{space 4}-.2665006{col 76}{space 3} .3709191
{txt}{space 21} {c |}
{space 17}wave {c |}
survey wave 4 (2016)  {c |}{col 23}{res}{space 2}-.4417672{col 35}{space 2} .5285092{col 46}{space 1}   -0.84{col 55}{space 3}0.403{col 63}{space 4}-1.479276{col 76}{space 3} .5957419
{txt}{space 21} {c |}
{space 7}wave#c.threat5 {c |}
survey wave 4 (2016)  {c |}{col 23}{res}{space 2}-.0016721{col 35}{space 2} .1654122{col 46}{space 1}   -0.01{col 55}{space 3}0.992{col 63}{space 4}-.3263906{col 76}{space 3} .3230463
{txt}{space 21} {c |}
{space 15}female {c |}{col 23}{res}{space 2} .0663335{col 35}{space 2} .0600373{col 46}{space 1}    1.10{col 55}{space 3}0.270{col 63}{space 4}-.0515249{col 76}{space 3}  .184192
{txt}{space 18}Age {c |}{col 23}{res}{space 2}-.0044828{col 35}{space 2} .0027713{col 46}{space 1}   -1.62{col 55}{space 3}0.106{col 63}{space 4}-.0099231{col 76}{space 3} .0009574
{txt}{space 14}edu_age {c |}{col 23}{res}{space 2}-.0115667{col 35}{space 2} .0182202{col 46}{space 1}   -0.63{col 55}{space 3}0.526{col 63}{space 4}-.0473346{col 76}{space 3} .0242012
{txt}{space 21} {c |}
{space 10}SocialGrade {c |}
{space 18}C1  {c |}{col 23}{res}{space 2} .0868275{col 35}{space 2} .0709821{col 46}{space 1}    1.22{col 55}{space 3}0.222{col 63}{space 4}-.0525166{col 76}{space 3} .2261715
{txt}{space 18}C2  {c |}{col 23}{res}{space 2} .1885894{col 35}{space 2} .0958883{col 46}{space 1}    1.97{col 55}{space 3}0.050{col 63}{space 4} .0003524{col 76}{space 3} .3768264
{txt}{space 18}DE  {c |}{col 23}{res}{space 2} .1872123{col 35}{space 2} .1068991{col 46}{space 1}    1.75{col 55}{space 3}0.080{col 63}{space 4}-.0226399{col 76}{space 3} .3970645
{txt}{space 21} {c |}
{space 10}work_status {c |}
{space 3}working part time  {c |}{col 23}{res}{space 2}-.0872595{col 35}{space 2} .0768701{col 46}{space 1}   -1.14{col 55}{space 3}0.257{col 63}{space 4}-.2381622{col 76}{space 3} .0636431
{txt}{space 3}full time student  {c |}{col 23}{res}{space 2}-.1473455{col 35}{space 2} .1303726{col 46}{space 1}   -1.13{col 55}{space 3}0.259{col 63}{space 4}-.4032782{col 76}{space 3} .1085872
{txt}{space 13}retired  {c |}{col 23}{res}{space 2} .0855955{col 35}{space 2}  .089817{col 46}{space 1}    0.95{col 55}{space 3}0.341{col 63}{space 4}-.0907229{col 76}{space 3}  .261914
{txt}{space 10}unemployed  {c |}{col 23}{res}{space 2}-.4511037{col 35}{space 2} .2137414{col 46}{space 1}   -2.11{col 55}{space 3}0.035{col 63}{space 4}-.8706965{col 76}{space 3}-.0315109
{txt}{space 9}not working  {c |}{col 23}{res}{space 2} .1322073{col 35}{space 2} .1627045{col 46}{space 1}    0.81{col 55}{space 3}0.417{col 63}{space 4}-.1871957{col 76}{space 3} .4516102
{txt}{space 21} {c |}
{space 15}UKborn {c |}{col 23}{res}{space 2} .3077339{col 35}{space 2} .2666252{col 46}{space 1}    1.15{col 55}{space 3}0.249{col 63}{space 4}-.2156743{col 76}{space 3} .8311421
{txt}{space 11}authvalues {c |}{col 23}{res}{space 2} .2100135{col 35}{space 2} .0673253{col 46}{space 1}    3.12{col 55}{space 3}0.002{col 63}{space 4} .0778481{col 76}{space 3} .3421789
{txt}{space 14}selfest {c |}{col 23}{res}{space 2} .1295878{col 35}{space 2}  .119286{col 46}{space 1}    1.09{col 55}{space 3}0.278{col 63}{space 4}-.1045809{col 76}{space 3} .3637565
{txt}{space 16}_cons {c |}{col 23}{res}{space 2} 1.868967{col 35}{space 2} .6749359{col 46}{space 1}    2.77{col 55}{space 3}0.006{col 63}{space 4}   .54401{col 76}{space 3} 3.193925
{txt}{hline 22}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. 
. *********************************************************************
. * FIGURE 2 IN THE PAPER:                      
. *       Unstandardized OLS Coefficient Estimates and 95% Confidence Intervals of the Impact of Threats on Group Hostility; 
. *       Threats Entered Simultaneously and with Hostility Toward White British  
. *       (comparing 2011 to 2016) 
. *********************************************************************
. 
. * NOTE: to calculate whether the difference between the estimate for a threat in 2011 is different from the one for the same threat in 2016, 
. * we calculate p-values by using the following calculation: 
. * 2*normal(-abs((coef. threat[] 2011 - coef. threat[] 2016)/sqrt(std. err. threat[] 2011^2 + std. err. threat[] 2016^2)))
. * coefficient estimates and standard errors are taken from the estimates for Table A9A and A9B 
. 
. * Black British
. * Threat 1 (neighborhood safety)
. display 2*normal(-abs((.0931242 - .0094313)/sqrt(.0441536^2 + .0271298^2)))
{res}.10631219
{txt}
{com}. ** p-value: .10631219
. * Threat 2 (individual economic)
. display 2*normal(-abs((-.028872 - -.0073306)/sqrt(.0536764^2 + .0303376^2)))
{res}.72680591
{txt}
{com}. ** p-value: .72680591
. * Threat 3 (collective safety)
. display 2*normal(-abs((.0035125 - .0134799)/sqrt(.0450737^2 + .0292336^2)))
{res}.85281289
{txt}
{com}. ** p-value: .85281289
. * Threat 4 (cultural)
. display 2*normal(-abs((.1601322 - .1733378)/sqrt(.0350183^2 + .0237411^2)))
{res}.75493863
{txt}
{com}. ** p-value: .75493863
. * Threat 5 (collective economic)
. display 2*normal(-abs((-.0427327 - -.0291809)/sqrt(.044155^2 + .0288678^2)))
{res}.7972673
{txt}
{com}. ** p-value: .7972673
. 
. * Muslims
. * Threat 1 (neighborhood safety)
. display 2*normal(-abs((.0467731 - .0434108)/sqrt(.0542704^2 + .0310232^2)))
{res}.9571051
{txt}
{com}. ** p-value: .9571051
. * Threat 2 (individual economic)
. display 2*normal(-abs((.0079859 - -.0165672)/sqrt(.0578503^2 + .032668^2)))
{res}.71170255
{txt}
{com}. ** p-value: .71170255
. * Threat 3 (collective safety)
. display 2*normal(-abs((.0528585 - -.0210769)/sqrt(.0579981^2 + .0337497^2)))
{res}.2705406
{txt}
{com}. ** p-value: .2705406
. * Threat 4 (cultural)
. display 2*normal(-abs((.2817762 - .2187632)/sqrt(.0401248^2 + .0270418^2)))
{res}.19281956
{txt}
{com}. ** p-value: .19281956
. * Threat 5 (collective economic)
. display 2*normal(-abs((-.091037 - -.0850948)/sqrt(.057773^2 + .0319274^2)))
{res}.92826958
{txt}
{com}. ** p-value: .92826958
. 
. * East Europeans
. * Threat 1 (neighborhood safety)
. display 2*normal(-abs((.0023991 - .0242707)/sqrt(.0461429^2 + .0290284^2)))
{res}.68826694
{txt}
{com}. ** p-value: .68826694
. * Threat 2 (individual economic)
. display 2*normal(-abs((-.0019248 - -.0147153)/sqrt(.0526388^2 + .0339375^2)))
{res}.8381807
{txt}
{com}. ** p-value: .8381807
. * Threat 3 (collective safety)
. display 2*normal(-abs((.0711302 - .0018616)/sqrt(.0458891^2 + .0325065^2)))
{res}.21804269
{txt}
{com}. ** p-value: .21804269
. * Threat 4 (cultural)
. display 2*normal(-abs((.1500684 - .1815412)/sqrt(.0368581^2 + .0244506^2)))
{res}.47673685
{txt}
{com}. ** p-value: .47673685
. * Threat 5 (collective economic)
. display 2*normal(-abs((-.0189427 - -.0946823)/sqrt(.0423463^2 + .0313185^2)))
{res}.15042805
{txt}
{com}. ** p-value: .15042805
. 
. 
. *********************************************************************
. * FIGURE A2 IN THE APPENDIX:
. *       Unstandardized OLS Coefficient Estimates and 95% Confidence Intervals of the Impact of Threats on Group Hostility; 
. *       Threats Entered Simultaneously
. *       (comparing 2011 to 2016) 
. *********************************************************************
. 
. * NOTE: to calculate whether the difference between the estimate for a threat in 2011 is different from the one for the same threat in 2016, 
. * we calculate p-values by using the following calculation: 
. * 2*normal(-abs((coef. threat[] 2011 - coef. threat[] 2016)/sqrt(std. err. threat[] 2011^2 + std. err. threat[] 2016^2)))
. * coefficient estimates and standard errors are taken from the estimates for Table A8A and A8B 
. 
. * Black British
. * Threat 1 (neighborhood safety)
. display 2*normal(-abs((.0859609  - .0279043)/sqrt(.0410717 + .0289343^2)))
{res}.7767208
{txt}
{com}. ** p-value: .7767208
. * Threat 2 (individual economic)
. display 2*normal(-abs((-.0238519 - .0094857)/sqrt(.0528471^2 + .0317759^2)))
{res}.58876416
{txt}
{com}. ** p-value: .58876416
. * Threat 3 (collective safety)
. display 2*normal(-abs((.0102645 - .0219323)/sqrt(.0419237^2 + .0297984^2)))
{res}.82054326
{txt}
{com}. ** p-value: .82054326
. * Threat 4 (cultural)
. display 2*normal(-abs((.1744879 - .1827249)/sqrt(.0324962^2 + .0252254^2)))
{res}.84130136
{txt}
{com}. ** p-value: .84130136
. * Threat 5 (collective economic)
. display 2*normal(-abs((-.0243403 - -.0295574)/sqrt(.0456357^2 + .0308609^2)))
{res}.9245533
{txt}
{com}. ** p-value: .9245533
. 
. * Muslims
. * Threat 1 (neighborhood safety)
. display 2*normal(-abs((.0605185 - .0580361)/sqrt(.0522981^2 + .0311723^2)))
{res}.96747692
{txt}
{com}. ** p-value: .96747692
. * Threat 2 (individual economic)
. display 2*normal(-abs((.013024 - -.0038695)/sqrt(.0576534^2 + .0320915^2)))
{res}.79792968
{txt}
{com}. ** p-value: .79792968
. * Threat 3 (collective safety)
. display 2*normal(-abs((.0477734 - -.0138552)/sqrt(.0565146^2 + .0337392^2)))
{res}.34910616
{txt}
{com}. ** p-value: .34910616
. * Threat 4 (cultural)
. display 2*normal(-abs((.2787076 - .2262143)/sqrt(.0382944^2 + .0276221^2)))
{res}.26624709
{txt}
{com}. ** p-value: .26624709
. * Threat 5 (collective economic)
. display 2*normal(-abs((-.0825042 - -.08612)/sqrt(.0569595^2 + .0320962^2)))
{res}.95589601
{txt}
{com}. ** p-value: .95589601
. 
. * East Europeans
. * Threat 1 (neighborhood safety)
. display 2*normal(-abs((.001476 - .0331326)/sqrt(.0435333 ^2 + .0290603^2)))
{res}.54530726
{txt}
{com}. ** p-value: .54530726
. * Threat 2 (individual economic)
. display 2*normal(-abs((-.0082988 - -.0057098)/sqrt(.0517012^2 + .0337664^2)))
{res}.96655732
{txt}
{com}. ** p-value: .96655732
. * Threat 3 (collective safety)
. display 2*normal(-abs((.0871651 - .0070299)/sqrt(.0429424^2 + .0321793^2)))
{res}.13534661
{txt}
{com}. ** p-value: .13534661
. * Threat 4 (cultural)
. display 2*normal(-abs((.1690109 - .1840589)/sqrt(.0347753^2 + .0248407^2)))
{res}.72475295
{txt}
{com}. ** p-value: .72475295
. * Threat 5 (collective economic)
. display 2*normal(-abs((-.0090078 - -.0936237)/sqrt(.0423013^2 + .0317273^2)))
{res}.10954813
{txt}
{com}. ** p-value: .10954813
. 
. * White British
. * Threat 1 (neighborhood safety)
. display 2*normal(-abs((.0689058 - .0606374)/sqrt(.1072397^2 + .0276963^2)))
{res}.94049118
{txt}
{com}. ** p-value: .94049118
. * Threat 2 (individual economic)
. display 2*normal(-abs((-.0731835 - .0586692)/sqrt(.1157375^2 + .0292668^2)))
{res}.2693876
{txt}
{com}. ** p-value: .2693876
. * Threat 3 (collective safety)
. display 2*normal(-abs((.1586729 - .0158332)/sqrt(.1124717^2 + .0270404^2)))
{res}.2168976
{txt}
{com}. ** p-value: .2168976
. * Threat 4 (cultural)
. display 2*normal(-abs((.0454654 - .0230823)/sqrt(.090936^2 + .0237759^2)))
{res}.81177539
{txt}
{com}. ** p-value: .81177539
. * Threat 5 (collective economic)
. display 2*normal(-abs((.1086055 - -.0038212)/sqrt(.1126276^2 + .0287071^2)))
{res}.33339911
{txt}
{com}. ** p-value: .33339911
. 
. 
. *********************************************************************
. * TABLE A.6 IN THE APPENDIX:    
. *       Correlations between Group Hostility Scores, 2011 and 2016
. *********************************************************************
. 
.         cap program drop ecorr
{txt}
{com}.         program ecorr, eclass
{txt}  1{com}.                 version 12
{txt}  2{com}.                 syntax [varlist] [if] [in] [aw fw] [, * ]
{txt}  3{com}.                 if (`"`weight'"'!="") {c -(}
{txt}  4{com}.                         local wgt `weight'`exp'
{txt}  5{com}.                 {c )-}
{txt}  6{com}.                 marksample touse
{txt}  7{com}.                 correlate `varlist' `if' `in' `wgt', `options'
{txt}  8{com}.                 tempname b V
{txt}  9{com}.                 mata: st_matrix("`b'", vech(st_matrix("r(C)"))')
{txt} 10{com}.                 local p = colsof(`b')
{txt} 11{com}.                 mat `V' = J(`p',`p',0)
{txt} 12{com}.                 local cols: colnames `b'
{txt} 13{com}.                 mat rownames `V' = `cols'
{txt} 14{com}.                 eret post `b' `V' [`wgt'] , obs(`=r(N)') esample(`touse')
{txt} 15{com}.                 eret local cmd ecorr
{txt} 16{com}.                 eret local title "Lower-diagonal correlation matrix"
{txt} 17{com}.                 eret local vars "`varlist'"
{txt} 18{com}.         
.         end
{txt}
{com}. 
.         cap program drop micorr
{txt}
{com}.         program micorr, rclass
{txt}  1{com}.                 tempname esthold
{txt}  2{com}.                 _estimates hold `esthold', nullok restore
{txt}  3{com}.                 qui mi estimate, cmdok: ecorr `0'
{txt}  4{com}.                 tempname C_mi
{txt}  5{com}.                 mata: st_matrix("`C_mi'", invvech(st_matrix("e(b_mi)")'))
{txt}  6{com}.                 mat colnames `C_mi' = `e(vars)'
{txt}  7{com}.                 mat rownames `C_mi' = `e(vars)'
{txt}  8{com}.                 di
{txt}  9{com}.                 di as txt "Multiple-imputation estimate of the correlation matrix"      
{txt} 10{com}.                 di as txt "(obs=" string(e(N_mi),"%9.0g") ")"
{txt} 11{com}.                 matlist `C_mi'
{txt} 12{com}.                 return clear
{txt} 13{com}.                 ret matrix C_mi = `C_mi'
{txt} 14{com}. 
.         end
{txt}
{com}.         
. micorr GHblack GHMus GHEEur GHwhite if wave == 0
{res}
{txt}Multiple-imputation estimate of the correlation matrix
(obs=120)
{res}
{txt}{space 0}{space 0}{ralign 12:}{space 1}{c |}{space 1}{ralign 9:GHblack}{space 1}{space 1}{ralign 9:GHMus}{space 1}{space 1}{ralign 9:GHEEur}{space 1}{space 1}{ralign 9:GHwhite}{space 1}
{space 0}{hline 13}{c   +}{hline 11}{hline 11}{hline 11}{hline 11}
{space 0}{space 0}{ralign 12:GHblack}{space 1}{c |}{space 1}{ralign 9:{res:{sf:        1}}}{space 1}{space 1}{ralign 9:{res:{sf:{space 9}}}}{space 1}{space 1}{ralign 9:{res:{sf:{space 9}}}}{space 1}{space 1}{ralign 9:{res:{sf:{space 9}}}}{space 1}
{space 0}{space 0}{ralign 12:GHMus}{space 1}{c |}{space 1}{ralign 9:{res:{sf: .5964661}}}{space 1}{space 1}{ralign 9:{res:{sf:        1}}}{space 1}{space 1}{ralign 9:{res:{sf:{space 9}}}}{space 1}{space 1}{ralign 9:{res:{sf:{space 9}}}}{space 1}
{space 0}{space 0}{ralign 12:GHEEur}{space 1}{c |}{space 1}{ralign 9:{res:{sf: .6432457}}}{space 1}{space 1}{ralign 9:{res:{sf: .7170745}}}{space 1}{space 1}{ralign 9:{res:{sf:        1}}}{space 1}{space 1}{ralign 9:{res:{sf:{space 9}}}}{space 1}
{space 0}{space 0}{ralign 12:GHwhite}{space 1}{c |}{space 1}{ralign 9:{res:{sf: .2292752}}}{space 1}{space 1}{ralign 9:{res:{sf: .2418031}}}{space 1}{space 1}{ralign 9:{res:{sf: .1634867}}}{space 1}{space 1}{ralign 9:{res:{sf:        1}}}{space 1}

{com}. micorr GHblack GHMus GHEEur GHwhite if wave == 1
{res}
{txt}Multiple-imputation estimate of the correlation matrix
(obs=698)
{res}
{txt}{space 0}{space 0}{ralign 12:}{space 1}{c |}{space 1}{ralign 9:GHblack}{space 1}{space 1}{ralign 9:GHMus}{space 1}{space 1}{ralign 9:GHEEur}{space 1}{space 1}{ralign 9:GHwhite}{space 1}
{space 0}{hline 13}{c   +}{hline 11}{hline 11}{hline 11}{hline 11}
{space 0}{space 0}{ralign 12:GHblack}{space 1}{c |}{space 1}{ralign 9:{res:{sf:        1}}}{space 1}{space 1}{ralign 9:{res:{sf:{space 9}}}}{space 1}{space 1}{ralign 9:{res:{sf:{space 9}}}}{space 1}{space 1}{ralign 9:{res:{sf:{space 9}}}}{space 1}
{space 0}{space 0}{ralign 12:GHMus}{space 1}{c |}{space 1}{ralign 9:{res:{sf: .8187486}}}{space 1}{space 1}{ralign 9:{res:{sf:        1}}}{space 1}{space 1}{ralign 9:{res:{sf:{space 9}}}}{space 1}{space 1}{ralign 9:{res:{sf:{space 9}}}}{space 1}
{space 0}{space 0}{ralign 12:GHEEur}{space 1}{c |}{space 1}{ralign 9:{res:{sf: .7920181}}}{space 1}{space 1}{ralign 9:{res:{sf: .8081156}}}{space 1}{space 1}{ralign 9:{res:{sf:        1}}}{space 1}{space 1}{ralign 9:{res:{sf:{space 9}}}}{space 1}
{space 0}{space 0}{ralign 12:GHwhite}{space 1}{c |}{space 1}{ralign 9:{res:{sf: .4791419}}}{space 1}{space 1}{ralign 9:{res:{sf: .3814397}}}{space 1}{space 1}{ralign 9:{res:{sf: .3811909}}}{space 1}{space 1}{ralign 9:{res:{sf:        1}}}{space 1}

{com}. 
{txt}end of do-file

{com}. 
. 
. 
. 
. 
. 
. 
. log close
      {txt}name:  {res}<unnamed>
       {txt}log:  {res}F:\My files\Survey experiment\Decoupling research note\Analysis\May 2017 resubmitted replication files\De Rooij et al. 2017 PSRM replication log_May 5 2017.smcl
  {txt}log type:  {res}smcl
 {txt}closed on:  {res} 5 May 2017, 13:13:55
{txt}{.-}
{smcl}
{txt}{sf}{ul off}